Publications

Published in 2024: 

December -2024 Published Paper

• Saxena, S., Panda, S., Tiwari, E., Singh, R., Fouda, M. M., Kalra, M. K., ... & Suri, J. S. (2024). Navigating the Artificial Intelligence Revolution in NeuroOncology: A Multidisciplinary Viewpoint. Neurocomputing, 129220. https://doi.org/10.1016/j.neucom.2024.129220.
• Raghupathy, B. K., Vairavasundaram, S., Ganesan, M., Namachivayam, R. K., Kotecha, K., & Herencsar, N. (2024). Enhanced Quantum Convolutional Neural Network for Signature Authentication in Consumer Products. IEEE Transactions on Consumer Electronics. https://doi.org/10.1109/TCE.2024.3509624
• Rajasekar, E., Chandra, H., Pears, N., Vairavasundaram, S., & Kotecha, K. (2025). Lung image quality assessment and diagnosis using generative autoencoders in unsupervised ensemble learning. Biomedical Signal Processing and Control, 102, 107268. https://doi.org/10.1016/j.bspc.2024.107268
• Joshi, V. C., Mehta, M. A., & Kotecha, K. (2024). White blood cell segmentation using U-Net and its variants to improve leukemia diagnosis. Neural Computing and Applications, 1-22. https://doi.org/10.1007/s00521-024-10757-3
• Dave, N. R., Mehta, M. A., & Kotecha, K. (2024). Effective Stemmers Using Trie Data Structure for Enhanced Processing of Gujarati Text. International Journal of Computational Intelligence Systems, 17(1), 309. https://doi.org/10.1007/s44196-024-00679-2
• Joshi, A., Pradhan, B., Chakraborty, S., Varatharajoo, R., Gite, S., & Alamri, A. (2024). Deep-Transfer-Learning Strategies for Crop Yield Prediction Using Climate Records and Satellite Image Time-Series Data. Remote Sensing, 16(24), 4804. https://doi.org/10.3390/rs16244804
• Khalate, P., Gite, S., Pradhan, B., & Lee, C. W. (2024). Advancements and gaps in natural language processing and machine learning applications in healthcare: a comprehensive review of electronic medical records and medical imaging. Frontiers in Physics, 12, 1445204. https://doi.org/10.3389/fphy.2024.1445204

November -2024 Published Paper

• Kumarappan, J., Rajasekar, E., Vairavasundaram, S., Kotecha, K., & Kulkarni, A. (2024). Federated Learning Enhanced MLP–LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction. International Journal of Computational Intelligence Systems, 17(1), 267. https://doi.org/10.1007/s44196-024-00680-9.
• Kumarappan, J., Rajasekar, E., Vairavasundaram, S., Kotecha, K., & Kulkarni, A. (2024). Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions. Journal of Big Data, 11(1), 154 https://doi.org/10.1186/s40537-024-01016-2
• Al-Najjar, H. A., Pradhan, B., He, X., Sheng, D., Alamri, A., Gite, S., & Park, H. J. (2024). Integrating Physical and Machine Learning Models for Enhanced Landslide Prediction in Data-Scarce Environments. Earth Systems and Environment, 1-28 https://doi.org/10.1007/s41748-024-00508-8
• Balgude SD, Gite S, Pradhan B, Lee C. 2024. Artificial intelligence and machine learning approaches in cerebral palsy diagnosis, prognosis, and management: a comprehensive review. PeerJ Computer Science 10:e2505 https://doi.org/10.7717/peerj-cs.2505

October -2024 Published Paper 

• Khan, N. A., Hussain, S., Spratford, W., Goecke, R., Kotecha, K., & Jamwal, P. (2024). Deep Learning-Driven Analysis of a Six-Bar Mechanism for Personalized Gait Rehabilitation. Journal of Computing and Information Science in Engineering, 1-23. https://doi.org/10.1115/1.4066859.
• Priyadharshini, S., Ramkumar, K., Vairavasundaram, S., Narasimhan, K., Venkatesh, S., Madhavasarma, P., & Kotecha, K. (2024). Bio-inspired feature selection for early diagnosis of Parkinson’s disease through optimization of deep 3D nested learning. Scientific Reports, 14(1), 23394. https://doi.org/10.1038/s41598-024-74405-5
• Jain, P., Sar, A., Choudhury, T., Singh, V., & Kotecha, K. (2023, December). Differentiation of Music Genre from an Audio File Using Neural Networks. In International Conference on Information Systems and Management Science (pp. 482-490). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-70789-6_40
• Ashtagi, R., Akkalkot, A. I., Kotecha, K., Maginmani, U. H., Patil, P., & Patil, A. (2024, April). Detection of Stage of Cancer Using Machine Learning and Deep Learning. In International Conference on Advances in Information Communication Technology & Computing (pp. 607-619). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-6103-6_38
• S. Khairnar, S. Gite, K. Mahajan, B. Pradhan, A. Alamri and S. D. Thepade, "Advanced Techniques for Biometric Authentication: Leveraging Deep Learning and Explainable AI," in IEEE Access, https://doi.org/10.1109/ACCESS.2024.3474690.

September -2024 Published Paper

• Sivamayilvelan, K., Rajaseker, E., Balachandran, S., Kotecha, K., & Vairavasundaram, S. (2024). Data-driven Approach for identifying the factors related to debt collector performance. Journal of Open Innovation: Technology, Market, and Complexity, 100385. https://doi.org/10.1016/j.joitmc.2024.100385.
• Kamat, P., Kumar, S., & Kotecha, K. (2024). DeepTool: A Deep Learning Framework for Tool Wear Onset Detection and Remaining Useful Life Prediction. MethodsX, 102965. https://doi.org/10.1016/j.mex.2024.102965
• Singh, D., Marathe, A., Roy, S., Walambe, R., & Kotecha, K. (2024). Explainable Rotation-Invariant Self-Supervised Representation Learning. MethodsX, 102959. https://doi.org/10.1016/j.mex.2024.102959
• Divyeshkumar Joshi, D., Kumar, S., Patil, S., Kamat, P., Kolhar, S., & Kotecha, K. Deep Learning with Ensemble Approach for Early Pile Fire Detection Using Aerial Images. Frontiers in Environmental Science, 12, 1440396. https://doi.org/10.3389/fenvs.2024.1440396
• Warke, V., Kumar, S., Bongale, A., Kotecha, K., & Abraham, A. (2024). Enhancement of tool life using magneto-rheological fluid damping and tool wear prediction through deep learning model in milling. Engineering Applications of Artificial Intelligence, 137, 109265. https://doi.org/10.1016/j.engappai.2024.109265
• Kumar, S., Sayyad, S., & Bongale, A. (2024). Fault Classification of 3D-Printing Operations Using Different Types of Machine and Deep Learning Techniques. AI, 5(4), 1759-1778. https://doi.org/10.3390/ai5040087
• Khanna, A., Jain, S., Choudhury, T., Kotecha, K., & Sar, A. (2024, March). AI-Driven Prediction of Medicinal Property Presence in Plants Cultivated with Nutrient-Enriched Manure. In International Conference On Emerging Trends In Expert Applications & Security (pp. 73-82). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3991-2_6
• Tiwari, S., Choudhury, T., & Kotecha, K. (2024, March). Ensembling of Transfer Learning for Enhanced Precision Agriculture in Plant Disease Classification. In International Conference On Emerging Trends In Expert Applications & Security (pp. 135-144). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3991-2_12
• Mall, P., Raina, D., Choudhury, T., Kotecha, K., & Sar, A. (2024, March). An Insight on Role of Artificial Intelligence for Detection of Parkinson’s Disease. In International Conference On Emerging Trends In Expert Applications & Security (pp. 117-125). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3991-2_10
• Prithviraj, Prasad, M. G., Choudhury, T., Kotecha, K., Jain, D., & Davanageri, A. M. (2024, July). A Novel Framework of Smart Security System Based on Machine Learning Techniques. In International Conference on Intelligent and Fuzzy Systems (pp. 133-144). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-67192-0_18
• Marathe, A., Desai, A., Walambe, R., & Kotecha, K. (2024, July). Identifying and Mitigating Bias in AI-Generated Image Datasets for Better Cognitive Understanding. In International Conference on Intelligent and Fuzzy Systems (pp. 176-184). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-70018-7_20
• Desai, A., Shah, B., Maheshwari, H., Walambe, R., & Kotecha, K. (2024, March). Posture Identification and Detection for Understanding Cognitive Behavior. In 2024 IEEE International Conference on Contemporary Computing and Communications (InC4) (Vol. 1, pp. 1-5). IEEE. https://doi.org/10.1109/InC460750.2024.10649274

August -2024 Published Paper

• Jain, D. K., Rahate, A., Joshi, G., Walambe, R., & Kotecha, K. (2022). Employing Co-learning to evaluate the Explainability of multimodal sentiment analysis. IEEE Transactions on Computational Social Systems. https://10.1109/TCSS.2022.3176403.
• Vijayakumar, A., Vairavasundaram, S., Koilraj, J. A. S., Rajappa, M., Kotecha, K., & Kulkarni, A. (2024). Real-time visual intelligence for defect detection in pharmaceutical packaging. Scientific Reports, 14(1), 18811. https://doi.org/10.1038/s41598-024-69701-z
• Priyadharshini, S., Ramkumar, K., Vairavasundaram, S., Narasimhan, K., Venkatesh, S., Amirtharajan, R., & Kotecha, K. (2024). A Comprehensive framework for Parkinson’s disease diagnosis using explainable artificial intelligence empowered machine learning techniques. Alexandria Engineering Journal, 107, 568-582. https://doi.org/10.1016/j.aej.2024.07.106
• Kusal, S. D., Patil, S. G., Choudrie, J., & Kotecha, K. V. (2024). Understanding the performance of AI algorithms in Text-Based Emotion Detection for Conversational Agents. ACM Transactions on Asian and Low-Resource Language Information Processing. https://doi.org/10.1145/3643133
• Garg, A., Garg, N. B., Jain, A., Choudhury, T., & Kotecha, K. (2023, December). A Machine Learning Approach to Cardiovascular Disease Prevention in Smart Healthcare. In International Conference on Cyber Intelligence and Information Retrieval (pp. 169-178). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3594-5_14
• Unfolding Conversational Artificial Intelligence: A Systematic Review of Datasets, Techniques and Challenges in DevelopmentsS Gite, U Rawat, S Kumar, B Saini, A Bhatt, K Kotecha…- Engineered Science, 2024 https://doi.org/10.30919/es1210
• Nedbal, C., Adithya, S., Gite, S., Naik, N., Griffin, S., & Somani, B. K. (2024). A Machine Learning Predictive Model for Ureteroscopy Lasertripsy Outcomes in a Pediatric Population—Results from a Large Endourology Tertiary Center. Journal of Endourology. https://doi.org/10.1089/end.2024.0120
• Garg, A., Garg, N. B., Bansal, M., Jain, A., Choudhury, T., & Kotecha, K. (2024, January). Utilizing Machine Learning-Based Algorithms to Predict Student’s Future. In International Conference on Universal Threats in Expert Applications and Solutions (pp. 439-446). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3810-6_36
• Joshi, P., Sati, S., Choudhury, T., Bajaj, T., Kotecha, K., & Sar, A. (2024, January). Classification of Venomous and Non-venomous Snakes Using Transfer Learning with MobileNetV2. In International Conference on Universal Threats in Expert Applications and Solutions (pp. 427-438). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3810-6_35

July-2024 Published Paper

• Tabatabaei, S., Bulgarova, B. A., Kotecha, K., Patil, S., Volkova, I. I., & Barabash, V. V. (2024). Digital citizenship and paradigm shift in generation z’s emotional communication: Social media’s role in shaping Iranian familial bonds. Journal of Infrastructure, Policy and Development, 8(7), 5443. https://doi.org/10.24294/jipd.v8i7.5443.
• Sharma, M., Rawat, S., Kumar, D., Awasthi, A., Sarkar, A., Sidola, A., ... & Kotecha, K. (2024). The state of the Yamuna River: a detailed review of water quality assessment across the entire course in India. Applied Water Science, 14(8), 175. https://doi.org/10.1007/s13201-024-02227-x
• Nedbal, C., Adithya, S., Gite, S., Naik, N., Griffin, S., & Somani, B. K. (2024). A Machine Learning (ML) Predictive Model for Ureteroscopy lasertripsy (URSL) Outcomes in a Paediatric Population–Results from a large Endourology Tertiary Centre. Journal of Endourology, (ja). https://doi.org/10.1089/end.2024.0120
• Yadav, R. K., Sharma, S., Patil, A., Jayaswal, R., Patil, S., & Kotecha, K. Dysphonia Measurements for Diagnosis of Parkinson’s Disease Using Optimized Machine Learning Techniques. https://doi.org/10.1049/icp.2024.0529
• Garg, A., Garg, N. B., Jain, A., Choudhury, T., & Kotecha, K. (2023, December). A Machine Learning Approach to Cardiovascular Disease Prevention in Smart Healthcare. In International Conference on Cyber Intelligence and Information Retrieval (pp. 169-178). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3594-5_14
• Sar, A., Goel, A., Choudhury, T., Kotecha, K., & Bhattacharya, A. (2023, December). A Novel Framework for Automatic Plant Disease Detection Using Convolutional Neural Networks. In International Conference on Cyber Intelligence and Information Retrieval (pp. 483-497). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3594-5_40
• Sharma, H. K., Sar, A., Choudhury, T., Kotecha, K., Dutta, S., & Bhattacharya, A. (2023, December). A Novel Framework for Facial Emotion Detection Using Deep Learning Algorithms for HCI-Enabled System. In International Conference on Cyber Intelligence and Information Retrieval (pp. 15-29). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3594-5_2
• Balakrishnan, B., Chandran, K., Kannabiran, K., Chowdhury, S., Choudhury, T., & Kotecha, K. (2023, December). GIS-Based Analysis of Water Integrity Differences Within the Madurai Region. In International Conference on Cyber Intelligence and Information Retrieval (pp. 153-167). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3594-5_13

June-2024 Published Paper

• Mishra, P., Dash, R. K., Choudhury, T., & Kotecha, K. (2024). Optimizing Residual Energy and Delay in WSN Routing using Particle Swarm Optimization. Journal homepage: http://iieta. org/journals/isi, 29(2), 761-770. https://doi.org/10.18280/isi.290238.
• Jain, D. K., Eyre, Y. G. M., Kumar, A., Gupta, B. B., & Kotecha, K. (2024). Knowledge-based data processing for multilingual natural language analysis. ACM Transactions on Asian and Low-Resource Language Information Processing, 23(5), 1-16 https://dl.acm.org/doi/10.1145/3583686
• Bidwai, P., Gite, S., Pahuja, N., Pahuja, K., Kotecha, K., Jain, N., & Ramanna, S. (2024). Multimodal Image Fusion for the Detection of Diabetic Retinopathy Using Optimized Explainable AI-based Light GBM Classifier. Information Fusion, 102526 https://doi.org/10.1016/j.inffus.2024.102526
• Deshpande, S., Harikrishnan, R., & Walambe, R. (2024). POMDP-based Probabilistic Decision Making for Path Planning in Wheeled Mobile Robot. Cognitive Robotics https://doi.org/10.1016/j.cogr.2024.06.001
• Joshi, P., Sati, S., Sar, A., Aich, S., Choudhury, T., Kotecha, K., & Ozseven, T. (2024, May). An End-to-End Framework for Multi-Docs Chatbot using Llama2. In Proceedings of the Cognitive Models and Artificial Intelligence Conference (pp. 232-236). https://doi.org/10.1145/3660853.3660921
• Sar, A., Joshi, P., Sati, S., Choudhary, R., Aich, S., Choudhury, T., ... & Ozseven, T. (2024, May). A Novel End-to-End Framework for Story Generation Using Deep Neural Networks. In Proceedings of the Cognitive Models and Artificial Intelligence Conference (pp. 246-253). https://doi.org/10.1145/3660853.3660923
• Saxena, R., Upadhayay, A., Raj, G., Choudhury, T., Kotecha, K., Sar, A., & Ozseven, T. (2024, May). Analysis of Enhanced Hidden Markov Models for Improved Stock Market Price Forecasting and Prediction. In Proceedings of the Cognitive Models and Artificial Intelligence Conference (pp. 237-245) https://doi.org/10.1145/3660853.3660922
• Yadav, A., Sharma, V., Raj, G., Choudhury, T., Sar, A., Kotecha, K., & Ozseven, T. (2024, May). Transforming Dermatological Diagnosis: Deep Learning Approaches for Skin Disease Detection in the Digital Era. In Proceedings of the Cognitive Models and Artificial Intelligence Conference (pp. 254-262). https://doi.org/10.1145/3660853.3660924
• Gupta, A., Gupta, A., Raj, G., Choudhury, T., Sar, A., Kotecha, K., & Ozseven, T. (2024, May). Traffic Light Detection for Self-Driving Cars using the YOLOv8 architecture. In Proceedings of the Cognitive Models and Artificial Intelligence Conference (pp. 263-269) https://doi.org/10.1145/3660853.3660925
• Patil, S., Nankar, O., Gite, S., & Kotecha, K. (2024, January). Comparing Object Detection Models for Public Safety. In International Conference on Smart Computing and Communication (pp. 77-86). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-1313-4_7
• Sukumar, A., Desai, A., Singhal, P., Gokhale, S., Jain, D. K., Walambe, R., & Kotecha, K. Training Against Disguises: Addressing and Mitigating Bias in Facial Emotion Recognition with Synthetic Data. https://brosdocs.net/fg2024/W017.pdf

May-2024 Published Paper

• Hayat, A., Morgado-Dias, F., Choudhury, T., Singh, T. P., & Kotecha, K. FruitVision: A deep learning based automatic fruit grading system. https://doi.org/10.1515/opag-2022-0276.
• Jain, D. K., Ding, W., & Kotecha, K. (2023). Training fuzzy deep neural network with honey badger algorithm for intrusion detection in cloud environment. International Journal of Machine Learning and Cybernetics, 14(6), 2221-2237 https://doi.org/10.1007/s13042-022-01758-6
• Choudhary, V., Tanwar, S., Choudhury, T., & Kotecha, K. (2024). Towards secure IoT networks: A comprehensive study of metaheuristic algorithms in conjunction with CNN using a self-generated dataset. MethodsX, 102747 https://doi.org/10.1016/j.mex.2024.102747
• Sasikumar, A., Ravi, L., Devarajan, M., Vairavasundaram, S., Kotecha, K., & Herencsar, N. (2024). Sustainable Electronics: A Blockchain-Empowered Digital Twin Based Governance System for Consumer Electronic Products. IEEE Transactions on Consumer Electronics https://doi.org/10.1109/TCE.2024.3394512
• Khemani, B., Patil, S., Kotecha, K., & Vora, D. (2024). Detecting health misinformation: A comparative analysis of machine learning and graph convolutional networks in classification tasks. MethodsX, 102737 https://doi.org/10.1016/j.mex.2024.102737
• Siraskar, R., Kumar, S., Patil, S., Bongale, A., & Kotecha, K. (2024). Application of the Nadaraya-Watson estimator based Attention Mechanism to the field of Predictive Maintenance. MethodsX, 102754 https://doi.org/10.1016/j.mex.2024.102754
• Bajaj, T., Parashar, S., Choudhury, T., & Kotecha, K. (2023, September). Framework for Reverse Supply Chain Using Sustainable Return Policy. In International Conference on Micro-Electronics and Telecommunication Engineering (pp. 523-538). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-99-9562-2_43
• Singh, K. U., Kumar, A., Kumar, G., Singh, T., Choudhury, T., & Kotecha, K. (2023, September). An Overview of the Use of Deep Learning Algorithms to Predict Bankruptcy. In International Conference on Micro-Electronics and Telecommunication Engineering (pp. 715-726). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-99-9562-2_59
• Sar, A., Choudhury, T., Bajaj, T., Kotecha, K., & de Marin, M. S. G. (2023, September). Airbnb Price Prediction Using Advanced Regression Techniques and Deployment Using Streamlit. In International Conference on Micro-Electronics and Telecommunication Engineering (pp. 685-698). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-99-9562-2_57

April-2024 Published Paper

• Ashtagi, Rashmi & Kotecha, Ketan & Padthe, Adithya & Shinde, Sandip & Chinchmalatpure, Sheela & Mane, Deepak. (2024). Design of an AI Layer for Real-Time Skin Cancer Diagnosis. Revue d'Intelligence Artificielle. 38. 377-385. https://doi.org/10.18280/ria.380201.
• Gupta, K., Aggarwal, S., Jha, A., Habib, A., Jagtap, J., Kolhar, S., ... & Choudhury, T. (2024). Deep Learning Framework for Liver Tumor Segmentation. EAI Endorsed Transactions on Pervasive Health and Technology, 10. https://doi.org/10.4108/eetpht.10.5561
• Ashisha, G. R., Mary, X. A., Chowdhury, S., Karthik, C., Choudhury, T., & Kotecha, K. (2023, December). Early Detection of Diabetes Using ML Based Classification Algorithms. In International Advanced Computing Conference (pp. 148-157). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56703-2_12
• Rani, P., Lamba, R., Sachdeva, R. K., Jain, A., Choudhury, T., & Kotecha, K. (2023, December). Diabetes Risk Prediction Through Fine-Tuned Gradient Boosting. In International Advanced Computing Conference (pp. 135-147). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56703-2_11
• Sachdeva, R. K., Singla, A., Bathla, P., Jain, A., Choudhury, T., & Kotecha, K. (2023, December). An Efficient Method for Heart Failure Diagnosis. In International Advanced Computing Conference (pp. 286-295). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56703-2_23

March-2024 Published Paper 

• Hasan, K. M. B., Sajid, M., Lapina, M. A., Shahid, M., & Kotecha, K. (2024). Blockchain technology meets 6 G wireless networks: A systematic survey. Alexandria Engineering Journal, 92, 199-220.https://doi.org/10.1016/j.aej.2024.02.031
• Mahadevkar, S., Patil, S., & Kotecha, K. (2024). Enhancement of handwritten text recognition using AI-based hybrid approach. MethodsX, 102654. https://doi.org/10.1016/j.mex.2024.102654
• S. Gupta, S. Gilotra, S. Rathi, T. Choudhury, K. Kotecha and T. Choudhury, "Plant Disease Recognition Using Different CNN Models," 2024 14th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 2024, pp. 787-792, https://doi.org/10.1109/Confluence60223.2024.10463383
• D. Khanduja, J. Mittal, T. Choudhury, K. Kotecha, M. Singh and S. Sinha, "Park-Space: A Parking Space Indicator," 2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, 2023, pp. 1-5,https://doi.org/10.1109/ICTBIG59752.2023.10455978
• V. Kumar, G. Kumar, S. Parashar, T. Choudhury and K. Kotecha, "A Comprehensive Examination of Satellite Stereo Triplet Image Matching for Digital Elevation Model (DEM) Generation," 2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, 2023, pp. 1-8https://doi.org/10.1109/ICTBIG59752.2023.10456056
• V. Sharma, A. Singh, Y. Prasad, S. Gupta, T. Choudhury and K. Kotecha, "Land Use and Land Cover Classification for Temporal Analysis on Ganjam District Region, Odisha Using Remote Sensing and Google Earth Engine," 2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, 2023, pp. 1-7https://doi.org/10.1109/ICTBIG59752.2023.10456228
• Singh, K. U., Kumar, A., Kumar, G., Choudhury, T., Singh, T., & Kotecha, K. (2023, December). Sentiment Analysis in Social Media Marketing: Leveraging Natural Language Processing for Customer Insights. In International Conference on Information and Communication Technology for Competitive Strategies (pp. 457-467). Singapore: Springer Nature Singaporehttps://doi.org/10.1007/978-981-99-9489-2_40
• Kumar, A., Singh, K. U., Kumar, G., Choudhury, T., Singh, T., & Kotecha, K. (2023, December). AI-Enable Heart Sound Analysis: PASCAL Approach for Precision-Driven Cardiopulmonary Assessment. In International Conference on Information and Communication Technology for Competitive Strategies (pp. 447-456). Singapore: Springer Nature Singapore.https://doi.org/10.1007/978-981-99-9489-2_39
• Ghosh, I., Gohel, R., Chakrabarti, S., Walambe, R., & Kotecha, K. (2023, June). Indian Agri-Exports to Select African Countries: A Machine Learning Approach to Gain Insights Towards Sustainable Food Security. In International Conference on Data Science and Big Data Analysis (pp. 261-272). Singapore: Springer Nature Singaporehttps://doi.org/10.1007/978-981-99-9179-2_20
• Farhat, S., Kumar, M., Vaish, A., Dewangan, B. K., Choudhury, T., & Kotecha, K. (2023, October). A Lightweight Encryption Method for Preserving E-Healthcare Data Privacy Using Dual Signature on Twisted Edwards Curves. In International Conference on Computer & Communication Technologies (pp. 69-82). Singapore: Springer Nature Singaporehttps://doi.org/10.1007/978-981-99-9707-7_7
• Mishra, V. K., Mishra, M., Dewangan, B. K., Parijatha, K., Choudhury, T., & Kotecha, K. (2023, October). Reinforcement Learning Approach to Solve: PBL Markov Model. In International Conference on Computer & Communication Technologies (pp. 333-342). Singapore: Springer Nature Singapore.https://doi.org/10.1007/978-981-99-9707-7_31
• Mishra, V. K., Mishra, M., Dewangan, B. K., Amulya, P., Choudhury, T., & Kotecha, K. (2023, October). Comparative Analysis of ARIMA Time Series Model and Other Techniques for Cloud Workloads Performance Prediction. In International Conference on Computer & Communication Technologies (pp. 343-350). Singapore: Springer Nature Singaporehttps://doi.org/10.1007/978-981-99-9707-7_32
• Singh, K. U., Kumar, A., Kumar, G., Singh, T., Choudhury, T., & Kotecha, K. (2023, October). Manufacturing In-House Information Technology Team Analysis Hybrid Software Development Model. In International Conference on Computer & Communication Technologies (pp. 371-379). Singapore: Springer Nature Singaporehttps://doi.org/10.1007/978-981-99-9707-7_35
• Dutta, C"., Singh, R., Garg, K., Choudhury, T., & Kotecha, K. (2023, October). An Optimized Hybrid Mechanism to Prevent Road Accidents in VANETs Using SVM and ANN. In International Conference on Computer & Communication Technologies (pp. 351-359). Singapore: Springer Nature Singaporehttps://doi.org/10.1007/978-981-99-9707-7_33
• Ghate, R., Walambe, R., Kalnad, N., & Kotecha, K. (2023, August). Real-Time Inferencing Using Transfer Learning for a Screening of Depression Detection Using Actigraphy. In International Conference on Artificial Intelligence on Textile and Apparel (pp. 327-336). Singapore: Springer Nature Singaporehttps://doi.org/10.1007/978-981-99-8476-3_27
• Singh, D., Kanathey, Y., Waykole, Y., Mishra, R. K., Walambe, R., Aqeel, K. H., & Kotecha, K. (2023, December). Exploring the Usability of Quantum Machine Learning for EEG Signal Classification. In International Advanced Computing Conference (pp. 427-438). Cham: Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-56700-1_34
• Thakur, S., Dhawan, R., Bhargava, P., Tripathi, K., Walambe, R., & Kotecha, K. (2023, December). The Forward-Forward Algorithm: Analysis and Discussion. In International Advanced Computing Conference (pp. 397-406). Cham: Springer Nature Switzerland https://doi.org/10.1007/978-3-031-56700-1_31

February-2024 Published Paper 

• Gawde, S., Patil, S., Kumar, S., Kamat, P., & Kotecha, K. (2024). An explainable predictive maintenance strategy for multi-fault diagnosis of rotating machines using multi-sensor data fusion. Decision Analytics Journal, 100425.https://doi.org/10.1016/j.dajour.2024.100425
• S. Gawde, S. Patil, S. Kumar, P. Kamat, K. Kotecha and S. Alfarhood, "Explainable Predictive Maintenance of Rotating Machines using LIME, SHAP, PDP, ICE," in IEEE Access, https://doi.org/doi:10.1109/ACCESS.2024.3367110
• Warke, V., Kumar, S., Bongale, A., & Kotecha, K. (2024). Robust Tool Wear Prediction using Multi-Sensor Fusion and Time-Domain Features for the Milling Process using Instance-based Domain Adaptation. Knowledge-Based Systems, 111454.https://doi.org/10.1016/j.knosys.2024.111454
• Subramanyam, S. P., Kotikula, D. K., Bennehalli, B., Babbar, A., Alamri, S., Duhduh, A. A., ... & Kotecha, K. (2024). Plain-Woven Areca Sheath Fiber-Reinforced Epoxy Composites: The Influence of the Fiber Fraction on Physical and Mechanical Features and Responses of the Tribo System and Machine Learning Modeling. ACS omega.https://doi.org/10.1021/acsomega.3c08164
• Mahadevkar, S., Patil, S., Kotecha, K., & Abraham, A. (2024). A comparison of deep transfer learning backbone architecture techniques for printed text detection of different font styles from unstructured documents. PeerJ Computer Science, 10, e1769https://doi.org/10.7717/peerj-cs.1769
• S. Verma, O. Pandey, T. Choudhury, A. Sar, K. Kotecha and T. Choudhury, "A Comprehensive Study on the Classification of the Edibility of Mushrooms," 2023 12th International Conference on System Modeling & Advancement in Research Trends (SMART), Moradabad, India, 2023, pp. 7-13, .https://doi.org/doi:10.1109/SMART59791.2023.10428619

January-2024 Published Paper

• Subramanian, N., Ravi, L., Shaan, M. J., Devarajan, M., Choudhury, T., Choudhury , T., Kotecha , K. & Vairavasundaram, S. (2024). Securing Mobile Devices from Malware: A Faceoff Between Federated Learning and Deep Learning Models for Android Malware Classification. Journal of Computer Science, 20(3), 254-264. https://doi.org/10.3844/jcssp.2024.254.264
• Garg, D., Dubey, N., Goel, P., Ramoliya, D., Ganatra, A., & Kotecha, K. (2024). Improvisation in Spinal Surgery Using AR (Augmented Reality), MR (Mixed Reality), and VR (Virtual Reality). Engineering Proceedings, 59(1), 186.https://doi.org/10.3390/engproc2023059186
• Agrawal, V., Jagtap, J., Patil, S., & Kotecha, K. (2024). Performance analysis of hybrid deep learning framework using a vision transformer and convolutional neural network for handwritten digit recognition. MethodsX, 102554https://doi.org/10.1016/j.mex.2024.102554
• Khemani, B., Patil, S., Kotecha, K., & Tanwar, S. (2024). A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions. Journal of Big Data, 11(1), 1-43https://doi.org/10.1186/s40537-023-00876-4
• Kamat, P., Kumar, S., Patil, S., & Kotecha, K. (2024). Anomaly-informed remaining useful life estimation (AIRULE) of bearing machinery using deep learning framework. MethodsX, 102555.https://doi.org/10.1016/j.mex.2024.102555
• Bidwai, P., Gite, S., Gupta, A., Pahuja, K., & Kotecha, K. (2024). Multimodal dataset using OCTA and Fundus Images for the study of Diabetic Retinopathy. Data in Brief, 110033.https://doi.org/10.1016/j.dib.2024.110033
• Kantipudi, M. P., Kumar, N. P., Aluvalu, R., Selvarajan, S., & Kotecha, K. (2024). An improved GBSO-TAENN-based EEG signal classification model for epileptic seizure detection. Scientific Reports, 14(1), 843.https://doi.org/10.1038/s41598-024-51337-8
• Mehta, A., Padaria, A. A., Bavisi, D., Ukani, V., Thakkar, P., Geddam, R., ... & Abraham, A. (2023). Securing the Future: A Comprehensive Review of Security Challenges and Solutions in Advanced Driver Assistance Systems. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3347200
• Agrawal, N., Pendharkar, I., Shroff, J., Raghuvanshi, J., Neogi, A., Patil, S., ... & Kotecha, K. (2024). A-XAI: adversarial machine learning for trustable explainability. AI and Ethics, 1-32https://doi.org/10.1007/s43681-023-00368-4
• Jagtap, S. S., VS, S. S., Kotecha, K., & Subramaniyaswamy, V. (2022). Securing Industrial Control Systems from Cyber-Attacks: A Stacked Neural-Network based Approach. IEEE Consumer Electronics Magazine.https://doi.org/10.1109/MCE.2022.3168997
• Sethi, A., Walambe, R., Jain, P., & Kotecha, K. (2023, October). Multimodal Mental Workload Classification Using Maus Dataset. In 2023 International Conference on Advanced Computing Technologies and Applications (ICACTA) (pp. 1-6). IEEE.https://doi.org/10.1109/ICACTA58201.2023.10393589
• Singh, K. U., Kumar, A., Kumar, G., Singh, T., Choudhury, T., & Kotecha, K. (2023, November). Optimizing Handwritten Numeral Recognition for English and Devanagari Using MNIST and CPAR Data. In 2023 7th International Symposium on Innovative Approaches in Smart Technologies (ISAS) (pp. 1-6). IEEE.https://doi.org/10.1109/ISAS60782.2023.10391793
• Singh, K. U., Kumar, A., Kumar, G., Choudhury, T., & Kotecha, K. (2023, November). MANET Routing Protocol Performance Comparison: DSDV, AODV, and DSR. In 2023 7th International Symposium on Innovative Approaches in Smart Technologies (ISAS) (pp. 1-7). IEEEhttps://doi.org/10.1109/ISAS60782.2023.10391760
• Kumar, A., Singh, K. U., Kumar, G., Choudhury, T., & Kotecha, K. (2023, November). Combating VoIP Spam: A Real-Time Algorithmic Approach. In 2023 7th International Symposium on Innovative Approaches in Smart Technologies (ISAS) (pp. 1-6). IEEE. IEEE.https://doi.org/10.1109/ISAS60782.2023.10391508
• Aggarwal, R., Aggarwal, E., Jain, A., Choudhury, T., & Kotecha, K. (2023, November). An Automation Perception for Cotton Crop Disease Detection Using Machine Learning. In 2023 7th International Symposium on Innovative Approaches in Smart Technologies (ISAS) (pp. 1-6). IEEE.https://doi.org/10.1109/ISAS60782.2023.10391530

Published in 2023: 

December-2023 Published Paper 

• Sharma, T., Kumar, A., Pant, S., & Kotecha, K. (2023). Wastewater Treatment and Multi-criteria Decision-Making Methods: A Review. IEEE Access.https://doi.org/10.30919/es1022
• Noronha, S. S., Mehta, M. A., Garg, D., Kotecha, K., & Abraham, A. (2023). Deep Learning-based Dermatological Condition Detection: A Systematic Review with Recent Methods, Datasets, Challenges and Future Directions. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3339635
• Agrawal, R., Walambe, R., Kotecha, K., Gaikwad, A., Deshpande, C. M., & Kulkarni, S. (2024). HVDROPDB datasets for research in retinopathy of prematurity. Data in Brief, 52, 109839.https://doi.org/10.1016/j.dib.2023.109839
• Kumar, D., Mehta, M. A., Joshi, V. C., Oza, R. S., Kotecha, K., & Lin, J. C. W. (2023). Empirical evaluation of filter pruning methods for acceleration of convolutional neural network. Multimedia Tools and Applications, 1-29.https://doi.org/10.1007/s11042-023-17656-0
• Joshi, S., Pushpad, V., Dutt, N., Pandey, Y., Choudhury, T., & Kotecha, K. (2023, October). Parhit: An Innovative Full-Stack Donation Platform with Dynamic-Routing Approach in ReactJS. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-6). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304893
• Rani, P., Lamba, R., Sachdeva, R. K., Jain, A., Choudhury, T., & Kotecha, K. (2023, October). Heart Disease Prediction Using Bayesian Optimized Classification Algorithms. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-5). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304966
• Sachdeva, R. K., Singh, K. D., Bathla, P., Jain, A., Choudhury, T., & Kotecha, K. (2023, October). Empowering Hepatitis Diagnosis Using RFE Feature Selection. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-5). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304999
• Choudhury, T., Singh, K. U., Kumar, A., Kumar, G., Gite, S., & Kotecha, K. (2023, October). C-QoS-AOMDV: A Cluster Based QoS Aware Multipath Routing Protocol for MANET Using Hybrid Soft Computing Techniques. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-6). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304911
• Kumar, A., Singh, K. U., Kumar, G., Choudhury, T., & Kotecha, K. (2023, October). Customer Lifetime Value Prediction: Using Machine Learning to Forecast CLV and Enhance Customer Relationship Management. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-7). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304958
• Shrivastava, P., Tripathi, N., Dewangan, B. K., Singh, B. K., Choudhury, T., Kotecha, K., & Dewangan, S. (2023, October). Autonomic Computing Based Respiratory Disorders Assessment Using Speech Parameters: A Systematic Review. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-6). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304972
• Dewangan, S., Mundeja, P., Deshpande, B., Dewangan, B. K., Choudhury, T., & Kotecha, K. (2023, October). Electronic Equipment Waste Generated by Computers and its Effect on Public Health in India. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-6). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304954
• Pillay, A., Arya, M., Sar, S. K., Dewangan, B. K., Choudhury, T., Kotecha, K., & Dewangan, S. (2023, October). ML-Based Feature Selection Technique for Imbalanced Data Streams. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-7). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304929
• Arya, M., Dewangan, B. K., Choudhury, T., Kotecha, K., Dewangan, S., & Gaidhane, A. (2023, October). An Adaptive Streaming Feature Selection Technique for Classifying Non-Stationary Data Streams. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-7). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304890
• Garg, V. K., Singh, S., Dewangan, B. K., Choudhury, T., Kotecha, K., & Dewangan, S. (2023, October). Automation in Vehicle Tracking Through RFID & Bar Code System. In 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-6). IEEE.https://doi.org/10.1109/ISMSIT58785.2023.10304944

November-2023 Published Paper 

• Trivedi, Pawan & Jain, Digha & Gite, Shilpa & Kotecha, Ketan & Bhatt, Anant & Naik, Nithesh. (2023). Indian Legal Corpus (ILC): A Dataset for A dataset summariz-ing Indian Legal Proceeding using Natural Language. Engineered Science. 10.30919/es1022.https://doi.org/10.30919/es1022
• Lahande, P. V., Kaveri, P. R., Saini, J. R., Kotecha, K., & Alfarhood, S. (2023). Reinforcement Learning approach for optimizing Cloud Resource Utilization with Load Balancing. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3329557
• Warke, V., Kumar, S., Bongale, A., Kamat, P., Kotecha, K., Selvachandran, G., & Abraham, A. (2024). Improving the useful life of tools using active vibration control through data-driven approaches: A systematic literature review. Engineering Applications of Artificial Intelligence, 128, 107367.https://doi.org/10.1016/j.engappai.2023.107367
• Oza, R. S., Mehta, M. A., Kotecha, K., & Lin, J. C. W. (2023). Analytics of deep model-based spatiotemporal and spatial feature learning methods for surgical action classification. Multimedia Tools and Applications, 1-29.https://doi.org/10.1007/s11042-023-17344-z
• Tan, S. L., Selvachandran, G., Ding, W., Paramesran, R., & Kotecha, K. (2023). Cervical Cancer Classification From Pap Smear Images Using Deep Convolutional Neural Network Models. Interdisciplinary Sciences: Computational Life Sciences, 1-23.https://doi.org/10.1007/s12539-023-00589-5
• Deshpande, Nilkanth & Gite, Shilpa & Pradhan, Biswajeet & Alamri, Abdullah & Lee, Chang-Wook. (2023). A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database. Computer Modeling in Engineering & Sciences. 1-10. 10.32604/cmes.2023.030704.https://doi.org/10.32604/cmes.2023.030704

October-2023 Published Paper

• Sasikumar, A., Ravi, L., Devarajan, M., Vairavasundaram, S., Selvalakshmi, A., Kotecha, K., & Abraham, A. (2023). A Decentralized Resource Allocation in Edge Computing for Secure IoT Environments. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3325056
• Bhanage, D. A., Pawar, A. V., Kotecha, K., & Abrahim, A. (2023). Failure Detection Using Semantic Analysis and Attention-Based Classifier Model for IT Infrastructure Log Data. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3319438
• Jagtap, S. S., VS, S. S., Kotecha, K., & Subramaniyaswamy, V. (2022). Securing Industrial Control Systems from Cyber-Attacks: A Stacked Neural-Network based Approach. IEEE Consumer Electronics Magazine.https://doi.org/10.1109/MCE.2022.3168997
• Chillapalli, J., Gite, S., Saini, B., Kotecha, K., & Alfarhood, S. (2023). A Review of Diagnostic Strategies for Pulmonary Embolism Prediction in Computed Tomography Pulmonary Angiograms. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3319558
• Surana, A., Rathod, M., Gite, S., Patil, S., Kotecha, K., Selvachandran, G., ... & Abraham, A. (2023). An audio-based anger detection algorithm using a hybrid artificial neural network and fuzzy logic model. Multimedia Tools and Applications, 1-21.https://doi.org/10.1007/s11042-023-16815-7
• Shinde, R., Patil, S., Kotecha, K., Potdar, V., Selvachandran, G., & Abraham, A. (2022). Securing AI-based Healthcare Systems using Blockchain Technology: A State-of-the-Art Systematic Literature Review and Future Research Directions. arXiv preprint arXiv:2206.04793.https://doi.org/10.1002/ett.4884

September-2023 Published Paper 

• De, S. K., Banerjee, A., Majumder, K., Kotecha, K., & Abraham, A. (2023). Coverage Area Maximization using MOFAC-GA-PSO Hybrid Algorithm in Energy Efficient WSN design. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3313000
• Walambe, R., Chaudhary, P., Bajaj, A., Rathore, A. S., Jain, V., & Kotecha, K. (2023, April). Generative Adversarial Networks for Mitigating Bias in Disinformation. In 2023 IEEE International Conference on Contemporary Computing and Communications (InC4) (Vol. 1, pp. 1-6). IEEE.https://doi.org/10.1109/InC457730.2023.10262880

August-2023 Published Paper 

• Bhatt, P., Sethi, A., Tasgaonkar, V., Shroff, J., Pendharkar, I., Desai, A., ... & Jain, N. K. (2023). Machine learning for cognitive behavioral analysis: datasets, methods, paradigms, and research directions. Brain informatics, 10(1), 18.https://doi.org/10.1186/s40708-023-00196-6
• Jerrish, D. J., Nankar, O., Gite, S., Patil, S., Kotecha, K., Selvachandran, G., & Abraham, A. (2023). Deep learning approaches for lyme disease detection: leveraging progressive resizing and self-supervised learning models. Multimedia Tools and Applications, 1-38.https://doi.org/10.1007/s11042-023-16306-9
• Gite, S., Mane, D. T., Mane, V., Kale, S., & Dhotre, P. (2023). Region-based Network for Yoga Pose Estimation with Discriminative Fine-Tuning Optimization. International Journal of Intelligent Systems and Applications in Engineering, 11(10s), 166-184.https://ijisae.org/index.php/IJISAE/article/view/3243

July-2023 Published Paper 

• Saravanan, S., Ramkumar, K. A. N. N. A. N., Narasimhan, K., Subramaniyaswamy, V., Kotecha, K., & Abraham, A. (2023). Explainable Artificial Intelligence (EXAI) Models for Early Prediction of Parkinson’s Disease Based on Spiral and Wave Drawings. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3291406
• Devi, A., Ezhilarasie, R., Joseph, S., Kotecha, K., Abraham, A., & Vairavasundaram, S. (2023). An Improved Boykov’s Graph Cut-based Segmentation Technique for the Efficient Detection of Cervical Cancer. IEEE Access.https://doi.org/10.1109/ACCESS.2023.3295833
• Roy, S., Marathe, A., Walambe, R., & Kotecha, K. (2022, December). Self Supervised Learning for Classifying the Rotated Images. In International Advanced Computing Conference (pp. 17-24). Cham: Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-35644-5_2
• Saini, B., Venkatesh, D., Chaudhari, N., Shelake, T., Gite, S., & Pradhan, B. (2023, July). A comparative analysis of Indian sign language recognition using deep learning models. In Forum for Linguistic Studies (Vol. 5, No. 1, pp. 197-222).https://doi.org/10.18063/fls.v5i1.1617

June-2023 Published Paper

• Natu, M., Bachute, M., & Kotecha, K. (2023). HCLA_CBiGRU: Hybrid Convolutional Bidirectional GRU Based Model for Epileptic Seizure Detection. Neuroscience Informatics, 100135.https://www.sciencedirect.com/science/article/pii/S2772528623000201?via%3Dihub
• Kusal, S., Patil, S., Choudrie, J., Kotecha, K., Vora, D., & Pappas, I. (2023). A systematic review of applications of natural language processing and future challenges with special emphasis in text-based emotion detection. Artificial Intelligence Review, 1-87.https://link.springer.com/article/10.1007/s10462-023-10509-0
• Sayyad, S., Kumar, S., Bongale, A., Kotecha, K., & Abraham, A. (2023). Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time–Frequency-Based Features and Deep Learning Models. Sensors, 23(12), 5659.https://www.mdpi.com/1424-8220/23/12/5659
• Sasikumar, A., Ravi, L., Kotecha, K., Abraham, A., Devarajan, M., & Vairavasundaram, S. (2023). A Secure Big Data Storage Framework based on Blockchain Consensus Mechanism with Flexible Finality. IEEE Access.DOI: 10.1109/ACCESS.2023.3282322
• Dave, N. R., Mehta, M. A., & Kotecha, K. (2023). A Systematic Review of Stemmers of Indian and Non-Indian Vernacular Languages. ACM Transactions on Asian and Low-Resource Language Information Processing.https://dl.acm.org/doi/10.1145/3604612
• Bhandari, N., Walambe, R., Kotecha, K., & Kaliya, M. (2023). Integrative gene expression analysis for the diagnosis of Parkinson’s disease using machine learning and explainable AI. Computers in Biology and Medicine, 107140.https://www.sciencedirect.com/science/article/abs/pii/S0010482523006054?via%3Dihub
• Marathe, A., Ramanan, D., Walambe, R., & Kotecha, K. (2023). WEDGE: A multi-weather autonomous driving dataset built from generative vision-language models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3317-3326).

May-2023 Published Paper

• Vignesh, N., Bhuvaneswari, S., Kotecha, K., & Subramaniyaswamy, V. (2023, May). Hybrid Diet Recommender System Using Machine Learning Technique. In Hybrid Intelligent Systems: 22nd International Conference on Hybrid Intelligent Systems (HIS 2022), December 13–15, 2022 (pp. 106-115). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-27409-1_10
• Hiwale, M., Walambe, R., Potdar, V., & Kotecha, K. (2023). A systematic review of privacy-preserving methods deployed with blockchain and federated learning for the telemedicine. Healthcare Analytics, 100192.https://doi.org/10.1016/j.health.2023.100192

April-2023 Published Paper

• Vignesh, N., Bhuvaneswari, S., Kotecha, K., & Subramaniyaswamy, V. (2023, May). Hybrid Diet Recommender System Using Machine Learning Technique. In Hybrid Intelligent Systems: 22nd International Conference on Hybrid Intelligent Systems (HIS 2022), December 13–15, 2022 (pp. 106-115). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-27409-1_10
• Hiwale, M., Walambe, R., Potdar, V., & Kotecha, K. (2023). A systematic review of privacy-preserving methods deployed with blockchain and federated learning for the telemedicine. Healthcare Analytics, 100192.https://doi.org/10.1016/j.health.2023.100192
• Joshi, A., Pradhan, B., Gite, S., & Chakraborty, S. (2023). Remote-Sensing Data and Deep-Learning Techniques in Crop Mapping and Yield Prediction: A Systematic Review. Remote Sensing, 15(8), 2014. https://doi.org/10.3390/rs15082014

March-2023 Published Paper

• Siraskar, R., Kumar, S., Patil, S., Bongale, A., & Kotecha, K. (2023). Reinforcement learning for predictive maintenance: a systematic technical review. Artificial Intelligence Review, 1-63. https://doi.org/10.1007/s10462-023-10468-6
• Gawde, S., Patil, S., Kumar, S., Kamat, P., Kotecha, K., & Abraham, A. (2022). Multi-fault diagnosis of industrial rotating machines using data-driven approach: A review of two decades of research. arXiv preprint arXiv:2206.14153. https://doi.org/10.1016/j.engappai.2023.106139
• Gaikwad, M., Ahirrao, S., Phansalkar, S., Kotecha, K., & Rani, S. (2023). Multi-Ideology, Multiclass Online Extremism Dataset, and Its Evaluation Using Machine Learning. Computational Intelligence and Neuroscience, 2023. https://doi.org/10.1155/2023/4563145
• Tripathi, K. M., Kamat, P., Patil, S., Jayaswal, R., Ahirrao, S., & Kotecha, K. (2023). Gesture-to-Text Translation Using SURF for Indian Sign Language. Applied System Innovation, 6(2), 35.https://doi.org/10.3390/asi6020035
• Gite, S., Patil, S., Dharrao, D., Yadav, M., Basak, S., Rajendran, A., & Kotecha, K. (2023). Textual Feature Extraction Using Ant Colony Optimization for Hate Speech Classification. Big Data and Cognitive Computing, 7(1), 45. https://doi.org/10.3390/bdcc7010045
• Walambe, R., Srivastava, A., Yagnik, B., Hasan, M., Saiyed, Z., Joshi, G., & Kotecha, K. (2022). Explainable misinformation detection across multiple social media platforms. arXiv preprint arXiv:2203.11724.https://10.1109/ACCESS.2023.3251892
• Jain, D. K., Zhao, X., González-Almagro, G., Gan, C., & Kotecha, K. (2023). Multimodal pedestrian detection using metaheuristics with deep convolutional neural network in crowded scenes. Information Fusion, 95, 401-414. https://doi.org/10.1016/j.inffus.2023.02.014
• Gupta, M., Gupta, B., Jabbari, A., Budhiraja, I., Garg, D., Kotecha, K., & Iwendi, C. A Novel Computer Assisted Genomic Test Method to Detect Breast Cancer in Reduced Cost and Time Using Ensemble Technique.https://doi.org/10.22967/HCIS.2023.13.008

February-2023 Published Paper

• Maheshwari, S., Jain, P. K., & Kotecha, K. (2023). Route Optimization of Mobile Medical Unit with Reinforcement Learning.Sustainability, 15(5), 3937. https://doi.org/10.3390/su15053937
• Ramesh, K., Warke, A. S., Kotecha, K., & Vajravelu, K. (2023). Numerical and artificial neural network modelling of magnetorheological radiative hybrid nanofluid flow with Joule heating effects.Journal of Magnetism and Magnetic Materials, 170552. https://doi.org/10.1016/j.jmmm.2023.170552
• Ashraf, Z., Shahid, M., Ahamd, F., Sajid, M., Kotecha, K., & Patil, S. (2023). A generalized multiobjective reliability redundancy allocation with uncertainties.IEEE Access. https://doi.org/10.1109/ACCESS.2023.3248800
• Guleria HV, Luqmani AM, Kothari HD, Phukan P, Patil S, Pareek P, Kotecha K, Abraham A, Gabralla LA. Enhancing the Breast Histopathology Image Analysis for Cancer Detection Using Variational Autoencoder.International Journal of Environmental Research and Public Health. 2023; 20(5):4244. https://doi.org/10.3390/ijerph20054244
• Srinivasan, B., Venkatesan, R., Aljafari, B., Kotecha, K., Indragandhi, V., & Vairavasundaram, S. (2023). A Novel Multicriteria Optimization Technique for VLSI Floorplanning Based on Hybridized Firefly and Ant Colony Systems.IEEE Access. https://doi.org/10.1109/ACCESS.2023.3244346
• Khairnar, S., Gite, S., Kotecha, K., & Thepade, S. D. (2023). Face Liveness Detection Using Artificial Intelligence Techniques: A Systematic Literature Review and Future Directions.Big Data and Cognitive Computing,7(1), 37. https://doi.org/10.3390/bdcc7010037
• Jasmine Pemeena Priyadarsini, M., Rajini, G. K., Hariharan, K., Utkarsh Raj, K., Bhargav Ram, K., Indragandhi, V., ... & Pandya, S. (2023). Lung Diseases Detection Using Various Deep Learning Algorithms.Journal of Healthcare Engineering,2023. https://doi.org/10.1155/2023/3563696
• Swaminathan, B., Palani, S., Vairavasundaram, S., Kotecha, K., & Kumar, V. (2022). IoT-Driven Artificial Intelligence Technique for Fertilizer Recommendation Model.IEEE Consumer Electronics Magazine,12(2), 109-117. https://doi.org/10.1109/MCE.2022.3151325

January -2023 Published Paper

• Singhal, P., Walambe, R., Ramanna, S., & Kotecha, K. (2023). Domain Adaptation: Challenges, Methods, Datasets, and Applications. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3237025
• Rajalakshmi, E., Elakkiya, R., Subramaniyaswamy, V., Alexey, L. P., Mikhail, G., Bakaev, M., ... & Abraham, A. (2023). Multi-Semantic Discriminative Feature Learning for Sign Gesture Recognition Using Hybrid Deep Neural Architecture. IEEE Access, 11, 2226-2238. https://doi.org/10.1109/ACCESS.2022.3233671
• PreetiBaser, Jatinderkumar R.Saini, KetanKotecha , TomConv: An Improved CNN Model for Diagnosis of Diseases in Tomato Plant Leaves, Procedia Computer Science ,Elsevier, https://doi.org/10.1016/j.procs.2023.01.160
• Jain, A., Aadithyanarayanan, M. R., Anand, A., Maheshwari, H., Gonge, S., Joshi, R., & Kotecha, K. (2023). Web Scanner: An Innovative Prototype for Checking Web Vulnerability. In Software Engineering Application in Systems Design: Proceedings of 6th Computational Methods in Systems and Software 2022, Volume 1 (pp. 680-691). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-21435-6_58

Published in 2022: 

• Patil, S., Varadarajan, V., Mahadevkar, S., Athawade, R., Maheshwari, L., Kumbhare, S., ... & Kotecha, K. (2022). Enhancing Optical Character Recognition on Images with Mixed Text Using Semantic Segmentation. Journal of Sensor and Actuator Networks, 11(4), 63. https://doi.org/10.3390/jsan11040063
• Mahadevkar, S. V., Khemani, B., Patil, S., Kotecha, K., Vora, D., Abraham, A., & Gabralla, L. A. (2022). A Review on Machine Learning Styles in Computer Vision-Techniques and Future Directions. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3209825
• Patil, S., Varadarajan, V., Mazhar, S. M., Sahibzada, A., Ahmed, N., Sinha, O., ... & Kotecha, K. (2022). Explainable Artificial Intelligence for Intrusion Detection System. Electronics, 11(19), 3079. https://doi.org/10.3390/electronics11193079
• Mahajan, S., Patil, S., Bhavnagri, M., Singh, R., Kalra, K., Saini, B., ... & Saini, J. (2022). Performance Analysis of Reinforcement Learning Techniques for Augmented Experience Training Using Generative Adversarial Networks. Applied Sciences 12(24), 12923. https://doi.org/10.3390/app122412923
• Paul, N., Tasgaonkar, V., Walambe, R., & Kotecha, K. (2022). Integrating the Generative Adversarial Network for Decision Making in Reinforcement Learning for Industrial Robot Agents. Robotics, 11(6), 150. https://doi.org/10.3390/robotics11060150
• Bidwai, P., Gite, S., Pahuja, K., & Kotecha, K. (2022). A Systematic Literature Review on Diabetic Retinopathy Using an Artificial Intelligence Approach. Big Data and Cognitive Computing, 6(4), 152. https://doi.org/10.3390/bdcc6040152
• Warke, V., Kumar, S., Bongale, A., & Kotecha, K. (2022). Design and evaluation of an MRF damper for semi-active vibration control of the machining processes. Journal of Instrumentation, 17(12), P12017.https://doi.org/10.1088/1748-0221/17/12/P12017
• Anton, J., Castelli, L., Chan, M. F., Outters, M., Tang, W. H., Cheung, V., ... & Kotecha, K. (2022). How Well Do Self-Supervised Models Transfer to Medical Imaging?. Journal of Imaging, 8(12), 320. https://doi.org/10.3390/jimaging8120320
• Hiwale M, Varadarajan V, Walambe R, Kotecha K. NikshayChain: A Blockchain-Based Proposal for Tuberculosis Data Management in India. Technologies. 2023; 11(1):5. https://doi.org/10.3390/technologies11010005
• Rajendran, A., Sahithi, V. S., Gupta, C., Yadav, M., Ahirrao, S., Kotecha, K., ... & Alhammad, S. (2022). Detecting Extremism on Twitter during US Capitol Riot Using Deep Learning Techniques. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3227962
• Tavse, S., Varadarajan, V., Bachute, M., Gite, S., & Kotecha, K. (2022). A Systematic Literature Review on Applications of GAN-Synthesized Images for Brain MRI. Future Internet, 14(12), 351. https://doi.org/10.3390/fi14120351
• Kadam, P., Vora, D., Mishra, S., Patil, S., Kotecha, K., Abraham, A., & Gabralla, L. A. (2022). Recent Challenges and Opportunities in Video Summarization with Machine Learning Algorithms. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3223379
• Sasikumar, A., Vairavasundaram, S., Kotecha, K., Indragandhi, V., Ravi, L., Selvachandran, G., & Abraham, A. (2022). Blockchain-based trust mechanism for digital twin empowered Industrial Internet of Things. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2022.11.002
• Bhandari, N., Walambe, R., Kotech, K., & Khare, S. (2022). Comprehensive survey of computational learning methods for analysis of gene expression data in genomics. arXiv preprint arXiv:2202.02958. https://doi.org/10.3389/fmolb.2022.907150
• Mahajan, S., Harikrishnan, R., & Kotecha, K. (2022). Adaptive Routing in Wireless Mesh Networks Using Hybrid Reinforcement Learning Algorithm. IEEE Access, 10, 107961-107979. https://doi.org/10.1109/ACCESS.2022.3210993
• Kumar, N. R., Krishnan, R. B., Manikandan, G., Subramaniyaswamy, V., & Kotecha, K. (2022). Reversible data hiding scheme using deep learning and visual cryptography for medical image communication. Journal of Electronic Imaging, 31(6), 063028. https://doi.org/10 .1117/1.JEI.31.6.063028
• Misra S, Kumar S, Sayyad S, Bongale A, Jadhav P, Kotecha K, Abraham A, Gabralla LA. Fault Detection in Induction Motor Using Time Domain and Spectral Imaging-Based Transfer Learning Approach on Vibration Data. Sensors. 2022; 22(21):8210.https://doi.org/10.3390/s22218210
• Magaraja, A. D., Rajapackiyam, E., Kanagaraj, V., Kanagaraj, S. J., Kotecha, K., Vairavasundaram, S., ... & Palade, V. (2022). A Hybrid Linear Iterative Clustering and Bayes Classification-Based GrabCut Segmentation Scheme for Dynamic Detection of Cervical Cancer. Applied Sciences, 12(20), 10522.https://doi.org/10.3390/app122010522
• Zope, B., Mishra, S., Shaw, K., Vora, D. R., Kotecha, K., & Bidwe, R. V. (2022). Question Answer System: A State-of-Art Representation of Quantitative and Qualitative Analysis. Big Data and Cognitive Computing, 6(4), 109. https://doi.org/10.3390/bdcc6040109
• Natarajan, B., Rajalakshmi, E., Elakkiya, R., Kotecha, K., Abraham, A., Gabralla, L.A., & Subramaniyaswamy, V. (2022). Development of an end-to-end deep learning framework for sign language recognition, translation, and video generation. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3210543
• Gaikwad, M., Ahirrao, S., Kotecha, K., & Abraham, A. (2022). Multi-Ideology Multi- Class Extremism Classification Using Deep Learning Techniques. IEEE Access, 10, 104829-104843.https://doi.org/10.1109/ACCESS.2022.3205744
• Gawde, S., Patil, S., Kumar, S., & Kotecha, K. (2022). A scoping review on multi-fault diagnosis of industrial rotating machines using multi-sensor data fusion. Artificial Intelligence Review, 1-54.https://doi.org/10.1007/s10462-022-10243-z
• Jena, R., Pradhan, B., Gite, S., Alamri, A., & Park, H. J. (2022). A new method to promptly evaluate spatial earthquake probability mapping using an explainable artificial intelligence (XAI) model. Gondwana Research.https://doi.org/10.1016/j.gr.2022.10.003
• Rathod, M., Dalvi, C., Kaur, K., Patil, S., Gite, S., Kamat, P., ... & Gabralla, L. A. (2022). Kids’ Emotion Recognition Using Various Deep-Learning Models with Explainable AI. Sensors, 22(20), 8066. https://doi.org/10.3390/s22208066
• Wagle, S. A., Varadarajan, V., & Kotecha, K. (2022). A New Compact Method Based on a Convolutional Neural Network for Classification and Validation of Tomato Plant Disease. Electronics, 11(19), 2994. https://doi.org/10.3390/electronics11192994
• Sanakkayala, D. C., Varadarajan, V., Kumar, N., Soni, G., Kamat, P., Kumar, S., ... & Kotecha, K. (2022). Explainable AI for Bearing Fault Prognosis Using Deep Learning Techniques. Micromachines, 13(9), 1471. https://doi.org/10.3390/mi13091471
• Choudhary, R., Walambe, R., & Kotecha, K. (2022). Spatial and temporal features unified self-supervised representation learning networks. Robotics and Autonomous Systems, 104256. https://doi.org/10.1016/j.robot.2022.104256
• Ahmad, F., Shahid, M., Alam, M., Ashraf, Z., Sajid, M., Kotecha, K., & Dhiman, G. (2022). Levelized Multiple Workflow Allocation Strategy under Precedence Constraints with Task Merging in IaaS Cloud Environment. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3202651
• Kusal, S., Patil, S., Choudrie, J., Kotecha, K., Mishra, S., & Abraham, A. (2022). AI-based Conversational Agents: A Scoping Review from Technologies to Future Directions. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3201144
• V. K. Menaria, A. Nayyar, S. Kumar and K. Kotecha, "Multiway relay based framework for network coding in multi-hop wsns," Computers, Materials & Continua, vol. 74, no.1, pp. 1199–1216, 2023. https://doi.org/10.32604/cmc.2023.032162
• Patil, S.; Varadarajan, V.; Mazhar, S.M.; Sahibzada, A.; Ahmed, N.; Sinha, O.; Kumar, S.; Shaw, K.; Kotecha, K. Explainable Artificial Intelligence for Intrusion Detection System. Electronics 2022, 11, 3079. https://doi.org/10.3390/electronics11193079
• Chavan, M.; Varadarajan, V.; Gite, S.; Kotecha, K. Deep Neural Network for Lung Image Segmentation on Chest X-ray. Technologies 2022, 10, 105. https://doi.org/10.3390/ technologies10050105
• Singamaneni, K. K., Juneja, A., Abd-Elnaby, M., Gulati, K., Kotecha, K., & Kumar, A. S. (2022). An Enhanced Dynamic Nonlinear Polynomial Integrity-Based QHCP-ABE Framework for Big Data Privacy and Security. Security and Communication Networks, 2022. https://doi.org/10.1155/2022/4206000
• Karn, A. L., Sengan, S., Kotecha, K., Pustokhina, I. V., Pustokhin, D. A., Subramaniyaswamy, V., & Buddhi, D. (2022). ICACIA: An Intelligent Context-Aware framework for COBOT in defense industry using ontological and deep learning models. Robotics and Autonomous Systems, 104234. https://doi.org/10.1016/j.robot.2022.104234
• Vyas, A. H., Mehta, M. A., Kotecha, K., Pandya, S., Alazab, M., & Gadekallu, T. R. (2022). Tear film breakup time-based dry eye disease detection using convolutional neural network. Neural Computing and Applications, 1-19.https://doi.org/10.1007/s00521-022-07652-0
• Sasikumar, A., Ravi, L., Kotecha, K., Indragandhi, V., & Subramaniyaswamy, V. (2022). Reconfigurable and hardware efficient adaptive quantization model-based accelerator for binarized neural network. Computers and Electrical Engineering, 102, 108302.https://doi.org/10.1016/j.compeleceng.2022.108302
• Zala, K., Thakkar, H. K., Jadeja, R., Singh, P., Kotecha, K., & Shukla, M. (2022). PRMS: Design and Development of Patients’ E-Healthcare Records Management System for Privacy Preservation in Third Party Cloud Platforms. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3198094
• Patel, V., Ramanna, S., Kotecha, K., & Walambe, R. (2022). Short Text Classification with Tolerance-Based Soft Computing Method. Algorithms, 15(8), 267. https://doi.org/ 10.3390/a15080267
• Zala, K., Thakkar, H. K., Jadeja, R., Dholakia, N. H., Kotecha, K., Jain, D. K., & Shukla, M. (2022). On the Design of Secured and Reliable Dynamic Access Control Scheme of Patient E-Healthcare Records in Cloud Environment. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/3804553
• Singh, R. R., Banerjee, S., Manikandan, R., Kotecha, K., Indragandhi, V., & Vairavasundaram, S. (2022). Intelligent IoT Wind Emulation System Based on Real-Time Data Fetching Approach. IEEE Access, 10, 78253-78267. https://doi.org/10.1109/ACCESS.2022.3193774
• Narkhede, P., Walambe, R., Chandel, P., Mandaokar, S., & Kotecha, K. (2022). MultimodalGasData: Multimodal Dataset for Gas Detection and Classification. Data, 7(8), 112. https://doi.org/10.3390/data7080112
• Singh, H., Rai, V., Kumar, N., Dadheech, P., Kotecha, K., Selvachandran, G., & Abraham, A. (2022). An enhanced whale optimization algorithm for clustering. Multimedia Tools and Applications, 1-20. https://doi.org/10.1007/s11042-022-13453-3
• Ramnath, G. S., Harikrishnan, R., Muyeen, S. M., & Kotecha, K. (2022). Household Electricity Consumer Classification Using Novel Clustering Approach, Review, and Case Study. Electronics, 11(15), 2302. https://doi.org/10.3390/electronics11152302
• Sayyad, S., Kumar, S., Bongale, A., Kotecha, K., Selvachandran, G., & Suganthan, P. N. (2022). Tool wear prediction using long short-term memory variants and hybrid feature selection techniques. The International Journal of Advanced Manufacturing Technology, 1-23. https://doi.org/10.1007/s00170-022-09784-y
• Kumar, R., Khepar, J., Yadav, K., Kareri, E., Alotaibi, S. D., Viriyasitavat, W., ... & Dhiman, G. (2022). A Systematic Review on Generalized Fuzzy Numbers and Its Applications: Past, Present and Future. Archives of Computational Methods in Engineering, 1-24. https://doi.org/10.1007/s11831-022-09779-8
• Jani, D., Varadarajan, V., Parmar, R., Bohara, M. H., Garg, D., Ganatra, A., & Kotecha, K. (2022). An Efficient Gait Abnormality Detection Method Based on Classification. Journal of Sensor and Actuator Networks, 11(3), 31. https://doi.org/10.3390/jsan11030031
• Sasikumar, A., Ravi, L., Kotecha, K., Saini, J. R., Varadarajan, V., & Subramaniyaswamy, V. (2022). Sustainable Smart Industry: A Secure and Energy Efficient Consensus Mechanism for Artificial Intelligence Enabled Industrial Internet of Things. Computational Intelligence and Neuroscience, 2022.https://doi.org/10.1155/2022/1419360
• Jain, S., Bhargava, C., Varadarajan, V., & Kotecha, K. (2022). “Fuzzy System Design Using Current Amplifier for 20nm CMOS Technology”.Computers, Materials &Amp; Continua,72(1), 1815-1829. doi: 10.32604/cmc.2022.024004
• Nilkanth Mukund Deshpande, Shilpa Gite, Biswajeet Pradhan, Mazen Ebraheem Assiri. “Explainable Artificial Intelligence–A New Step towards the Trust in Medical Diagnosis with AI Frameworks: A Review” , CMES-Computer Modeling in Engineering & Sciences, June 2022, https://www.techscience.com/CMES/online/detail/18706
• Hudnurkar, S., Sood, V., Mishra, V., Mehta, M., Upadhyay, A., Gite, S., & Rayavarapu, N. (2022). Multivariate Time Series Forecasting of Rainfall Using Machine Learning. In Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis (pp. 87-106). IGI Global., doi 10.4018/978-1-6684-3981-4.ch007
• Khade, S., Gite, S., & Pradhan, B. (2022). “Iris Liveness Detection Using Multiple Deep Convolution Networks". Big Data And Cognitive Computing, 6(2), 67. doi: 10.3390/bdcc6020067
• Wilta, F., Chong, A., Selvachandran, G., Kotecha K., & Ding, W. (2022). Generalized Susceptible–Exposed–Infectious–Recovered model and its contributing factors for analysing the death and recovery rates of the COVID-19 pandemic. Applied Soft Computing, 123, 108973. doi: 10.1016/j.asoc.2022.108973
• Raulji, J. K., Saini, J. R., Pal, K., & Kotecha, K. (2022). A Novel Framework for Sanskrit-Gujarati Symbolic Machine Translation System. International Journal of Advanced Computer Science and Applications, 13(4). doi:10.14569/IJACSA.2022.0130444
• Natarajan, S., Vairavasundaram, S., Kotecha, K., Indragandhi, V., Palani, S., Saini, J. R., & Ravi, L. (2022). CD-SemMF: Cross-Domain Semantic Relatedness Based Matrix Factorization Model Enabled with Linked Open Data for User Cold Start Issue. IEEE Access. doi: 10.1109/ACCESS.2022.3175566
• Samant, R. M., Bachute, M., Gite, S., & Kotecha, K. (2022). Framework for Deep Learning-Based Language Models using Multi-task Learning in Natural Language Understanding: A Systematic Literature Review and Future Directions. IEEE Access. DOI: 10.1109/ACCESS.2022.3149798
• Natu, M., Bachute, M., Gite, S., Kotecha, K., & Vidyarthi, A. (2022). Review on epileptic seizure prediction: machine learning and deep learning approaches. Computational and Mathematical Methods in Medicine, 2022. https://doi.org/10.1155/2022/7751263
• Veeramuthu, A., Meenakshi, S., Mathivanan, G., Kotecha, K., Saini, J. R., Vijayakumar, V., & Subramaniyaswamy, V. (2022). MRI Brain Tumor Image Classification Using a Combined Feature and Image-Based Classifier. Frontiers in sychology, 13. https://doi.org/10.3389/fpsyg.2022.848784
• Tailor, J. H., Rakholia, R., Saini, J. R., & Kotecha, K. (2022). Deep Learning Approach for Spoken Digit Recognition in Gujarati Language. International Journal of Advanced Computer Science and Applications, 13(4) http://dx.doi.org/10.14569/IJACSA.2022.0130450
• Barve, Y., Saini, J. R., Pal, K., & Kotecha, K. (2022). A Novel Evolving Sentimental Bag-of-Words Approach for Feature Extraction to Detect Misinformation. International Journal of Advanced Computer Science and Applications, 13(4). DOI : 10.14569/issn.2156-5570
• Modh, J. C., Saini, J. R., & Kotecha, K. (2022). A Novel Morphological Analysis based Approach for Dynamic Detection of Inflected Gujarati Idioms. International Journal of Advanced Computer Science and Applications, 13(4). doi: 10.14569/IJACSA.2022.0130422
• Kadam, P., Pandya, S., Phansalkar, S., Sarangdhar, M., Petkar, N., Kotecha, K., & Garg, D. (2022). FVEstimator: A novel food volume estimator Wellness model for calorie measurement and healthy living. Measurement, 111294. https://doi.org/10.1016/j.measurement.2022.111294
• Ali, F., Kumar, H., Patil, S., Kotecha, K., Banjar, A., & Daud, A. (2022). Target-DBPPred: An intelligent model for prediction of DNA-binding proteins using discrete wavelet transform based compression and light eXtreme gradient boosting. Computers in Biology and Medicine, 145, 105533. https://doi.org/10.1016/j.compbiomed.2022.105533
• Jagtap, S. S., VS, S. S., Kotecha, K., & Subramaniyaswamy, V. (2022). Securing Industrial Control Systems from Cyber-Attacks: A Stacked Neural-Network based Approach. IEEE Consumer Electronics Magazine. DOI: 10.1109/MCE.2022.3168997
• Bidwe, R. V., Mishra, S., Patil, S., Shaw, K., Vora, D. R., Kotecha, K., & Zope, B. (2022). Deep Learning Approaches for Video Compression: A Bibliometric Analysis. Big Data and Cognitive Computing, 6(2), 44. https://doi.org/10.3390/bdcc6020044
• Gayakwad, M., Patil, S., Kadam, A., Joshi, S., Kotecha, K., Joshi, R., ... & Shelke, M. (2022). Credibility Analysis of User-Designed Content Using Machine Learning Techniques. Applied System Innovation, 5(2), 43. https://doi.org/10.3390/asi5020043
• Sasikumar, A., Senthilkumar, N., Subramaniyaswamy, V., Kotecha, K., Indragandhi, V., & Ravi, L. (2022). An efficient, provably-secure DAG based consensus mechanism for industrial internet of things. International Journal on Interactive Design and Manufacturing (IJIDeM), 1-11. https://doi.org/10.1007/s12008-022-00890-5
• Mahajan, S., HariKrishnan, R., & Kotecha, K. (2022). Prediction of network traffic in wireless mesh networks using hybrid deep learning model. IEEE Access, 10, 7003-7015. DOI: 10.1109/ACCESS.2022.3140646
• Deotale, D., Verma, M., Suresh, P., & Kotecha, K. (2022). Optimized hybrid RNN model for human activity recognition in untrimmed video. Journal of Electronic Imaging, 31(5), 051409. https://doi.org/10.1117/1.JEI.31.5.051409
• Mishra, S., Shaw, K., Mishra, D., Patil, S., Kotecha, K., Kumar, S., & Bajaj, S. (2022). Improving the Accuracy of Ensemble Machine Learning Classification Models Using a Novel Bit-Fusion Algorithm for Healthcare AI Systems. Frontiers in Public Health, 10. doi: 10.3389/fpubh.2022.858282
• Mishra, A., Dharahas, G., Gite, S., Kotecha, K., Koundal, D., Zaguia, A., ... & Lee, H. N. (2022). ECG Data Analysis with Denoising Approach and Customized CNNs. Sensors, 22(5), 1928. doi: 10.3390/s22051928
• Pachouly, J., Ahirrao, S., & Kotecha, K. (2022). SDPTool: A tool for creating datasets and software defect predictions. SoftwareX, 18, 101036. https://doi.org/10.1016/j.softx.2022.101036
• Shroff, J., Walambe, R., Singh, S. K., & Kotecha, K. (2022). Enhanced Security Against Volumetric DDoS Attacks Using Adversarial Machine Learning. Wireless Communications and Mobile Computing, 2022. https://doi.org/10.1155/2022/5757164
• Banerjee, A., Garg, D., Das, V., Sahoo, L., Nath, I., Varadarajan, V., & Kotecha, K. (2022). Design of Energy Efficient WSN Using a Noble SMOWA Algorithm. CMC-COMPUTERS MATERIALS & CONTINUA, 72(2), 3585-3600. DOI: 10.32604/cmc.2022.025233
• Holkar, A., Walambe, R., & Kotecha, K. (2022). Few-Shot learning for face recognition in the presence of image discrepancies for limited multi-class datasets. Image and Vision Computing, 120, 104420. https://doi.org/10.1016/j.imavis.2022.104420
• Pachouly, J., Ahirrao, S., Kotecha, K., Selvachandran, G., & Abraham, A. (2022). A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools. Engineering Applications of Artificial Intelligence, 111, 104773. https://doi.org/10.1016/j.engappai.2022.104773

Published in 2021: 

• Bhatt, A. R., Ganatra, A., & Kotecha, K. (2021). Cervical cancer detection in pap smear whole slide images using convnet with transfer learning and progressive resizing. PeerJ Computer Science, 7, e348. https://peerj.com/articles/cs-348
• Bhatt, A., Ganatra, A., & Kotecha, K. (2021). COVID-19 pulmonary consolidations detection in chest X-ray using progressive resizing and transfer learning techniques. Heliyon, 7(6), e07211. doi: https://doi.org/10.1016/j.heliyon.2021.e07211
• Ghayvat, H., Awais, M., Gope, P., Pandya, S., & Majumdar, S. (2021). Recognizing suspect and predicting the spread of contagion based on mobile phone location data (counteract): a system of identifying covid-19 infectious and hazardous sites, detecting disease outbreaks based on the internet of things, edge computing, and artificial intelligence. Sustainable Cities and Society, 69, 102798. https://doi.org/10.1016/j.scs.2021.102798
• Mishra, N., & Pandya, S. (2021). Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review. IEEE Access, 9, 59353-59377. doi: https://doi.org/10.1109/ACCESS.2021.3073408..
• Mehta, P., Pandya, S., & Kotecha, K. (2021). Harvesting social media sentiment analysis to enhance stock market prediction using deep learning. PeerJ Computer Science, 7, e476.https://doi.org/10.7717/peerj-cs.476
• Pandya, S., Wakchaure, M. A., Shankar, R., & Annam, J. R. (2021). Analysis of NOMA-OFDM 5G wireless system using deep neural network. The Journal of Defense Modeling and Simulation, 1548512921999108. doi: https://doi.org/10.1177/1548512921999108
• Mishra, N., & Pandya, S. (2021). Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review. IEEE Access, 9, 59353-59377. https://doi.org/10.1109/ACCESS.2021.3073408
• Srivastava, A., Jain, S., Miranda, R., Patil, S., Pandya, S., & Kotecha, K. (2021). Deep learning based respiratory sound analysis for detection of chronic obstructive pulmonary disease. PeerJ Computer Science, 7, e369. https://peerj.com/articles/cs-369.pdf
• Bhandari, N., Khare, S., Walambe, R., & Kotecha, K. (2021). Comparison of machine learning and deep learning techniques in promoter prediction across diverse species. PeerJ Computer Science, 7, e365. https://doi.org/10.7717/peerj-cs.365
• Choudrie, J., Banerjee, S., Kotecha, K., Walambe, R., Karende, H., & Ameta, J. (2021). Machine learning techniques and older adults processing of online information and misinformation: A covid 19 study. Computers in human behavior, 119, 106716. https://doi.org/10.1016/j.chb.2021.106716
• Narkhede, P., Walambe, R., Mandaokar, S., Chandel, P., Kotecha, K., & Ghinea, G. (2021). Gas detection and identification using multimodal artificial intelligence based sensor fusion. Applied System Innovation, 4(1), 3.https://doi.org/10.3390/asi4010003
• Walambe, R., Kolhatkar, A., Ojha, M., Kademani, A., Pandya, M., Kathote, S., & Kotecha, K. (2020, December). Integration of explainable AI and blockchain for secure storage of human readable justifications for credit risk assessment. In International Advanced Computing Conference (pp. 55-72). Springer, Singapore.https://doi.org/10.3390/asi4010003
• Pandya, S., & Ghayvat, H. (2021). Ambient acoustic event assistive framework for identification, detection, and recognition of unknown acoustic events of a residence. Advanced Engineering Informatics, 47, 101238,https://doi.org/10.1016/j.aei.2020.101238.
• Patil, A., Bachute, M., & Kotecha, K. (2021). Identification and Classification of the Tea Samples by Using Sensory Mechanism and Arduino UNO. Inventions, 6(4), 94.https://doi.org/10.3390/inventions6040094
• Mahajan, S., HariKrishnan, R., & Kotecha, K. (2022). Prediction of network traffic in wireless mesh networks using hybrid deep learning model. IEEE Access, 10, 7003-7015. https://doi.org/10.1109/ACCESS.2022.3140646
• Bhargava, C., Sharma, P. K., & Kotecha, K. (2021). Lifetime estimation of tantalum capacitor for mobile applications using empirical and experimental techniques: a DOE approach. International Journal of Quality & Reliability Management, https://doi.org/10.1108/IJQRM-09-2021-0331
• Sarma, R., Bhargava, C., & Kotecha, K. An Evolutionary Normalization Algorithm for Signed Floating-Point Multiply-Accumulate Operation. Doi: https://doi.org/10.32604/cmc.2022.024516
• Mahanta, H. J., Nath, K., Roy, A. K., Kotecha, K., & Varadaranjan, V. (2021). Using Genetic Algorithm in Inner Product to Resist Modular Exponentiation From Higher Order DPA Attacks. IEEE Access, 10, 3238-3251. https://doi.org/10.1109/ACCESS.2021.3139925
• Tupe-Waghmare, P., Malpure, P., Kotecha, K., Beniwal, M., Santosh, V., Saini, J., & Ingalhalikar, M. (2021). Comprehensive genomic subtyping of glioma using semi-supervised multi-task deep learning on multimodal MRI. IEEE Access, 9, 167900-167910.https://doi.org/10.1109/ACCESS.2021.3136293
• Kumar, S., Kolekar, T., Kotecha, K., Patil, S., & Bongale, A. (2022). Performance evaluation for tool wear prediction based on Bi-directional, Encoder–Decoder and Hybrid Long Short-Term Memory models. International Journal of Quality & Reliability Management.https://doi.org/10.1108/IJQRM-08-2021-0291
• Kadam, K. D., Ahirrao, S., & Kotecha, K. (2022). Efficient approach towards detection and identification of copy move and image splicing forgeries using mask R-CNN with MobileNet V1. Computational Intelligence and Neuroscience, 2022.https://doi.org/10.1155/2022/6845326
• Sengan, S., Kotecha, K., Vairavasundaram, I., Velayutham, P., Varadarajan, V., Ravi, L., & Vairavasundaram, S. (2021). Real-Time Automatic Investigation of Indian Roadway Animals by 3D Reconstruction Detection Using Deep Learning for R-3D-YOLOV3 Image Classification and Filtering. Electronics, 10(24), 3079.https:// doi.org/10.3390/electronics10243079
• Devika, R., Vairavasundaram, S., Mahenthar, C. S. J., Varadarajan, V., & Kotecha, K. (2021). A Deep Learning Model Based on BERT and Sentence Transformer for Semantic Keyphrase Extraction on Big Social Data. IEEE Access, 9, 165252-165261.https://doi.org/10.1109/ACCESS.2021.3133651
• Elakkiya, R., Jain, D. K., Kotecha, K., Pandya, S., Reddy, S. S., Rajalakshmi, E., ... & Subramaniyaswamy, V. (2021). Hybrid Deep Neural Network for Handling Data Imbalance in Precursor MicroRNA. Frontiers in Public Health, 9. https://doi.org/10.3389/fpubh/2021/82141
• Mishra, N., Pandya, S., Patel, C., Cholli, N., Modi, K., Shah, P., ... & Kotecha, K. (2021). Memcached: An Experimental Study of DDoS Attacks for the Wellbeing of IoT Applications. Sensors, 21(23), 8071. https://doi.org/10.3390/s21238071
• Dalvi, C., Rathod, M., Patil, S., Gite, S., & Kotecha, K. (2021). A Survey of AI-Based Facial Emotion Recognition: Features, ML & DL Techniques, Age-Wise Datasets and Future Directions. Ieee Access, 9, 165806-165840. doi: https://doi.org/10.1109/ACCESS.2021.3131733
• Varadarajan, V., Garg, D., & Kotecha, K. (2021). An efficient deep convolutional neural network approach for object detection and recognition using a multi-scale anchor box in real-time. Future Internet, 13(12), 307. https://doi.org/10.3390/fi13120307
• Dhanaraj, R. K., Ramakrishnan, V., Poongodi, M., Krishnasamy, L., Hamdi, M., Kotecha, K., & Vijayakumar, V. (2021). Random Forest Bagging and X-Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data. Wireless Communications and Mobile Computing, 2021.https://doi.org/10.1155/2021/2730246
• Kotecha, K., Verma, R., Rao, P. V., Prasad, P., Mishra, V. K., Badal, T., ... & Sharma, S. (2021). Enhanced Network Intrusion Detection System. Sensors, 21(23), 7835. https://doi.org/10.3390/s21237835
• Bathla, G., Singh, P., Kumar, S., Verma, M., Garg, D., & Kotecha, K. (2021). Recop: Fine-grained Opinions and Collaborative Filtering based Recommender System for Industry 5.0.https://doi.org/10.1007/s00500-021-06590-8
• Shiralkar, K., Bongale, A., Kumar, S., Kotecha, K., & Prakash, C. (2021). Assessment of the benefits of information and communication technologies (ICT) adoption on downstream supply chain performance of the retail industry. Logistics, 5(4), 80., https://doi.org/10.3390/logistics5040080
• Gite, S., Mishra, A., & Kotecha, K. (2022). Enhanced lung image segmentation using deep learning. Neural Computing and Applications, 1-15.https://doi.org/10.1007/s00521-021-06719-8
• Jain, V., Nankar, O., Jerrish, D. J., Gite, S., Patil, S., & Kotecha, K. (2021). A novel AI-based system for detection and severity prediction of dementia using MRI. IEEE Access, 9, 154324-154346. https://doi.org/10.1109/ACCESS.2021.3127394
• Patil, A., Bachute, M., & Kotecha, K. (2021). Identification and Classification of the Tea Samples by Using Sensory Mechanism and Arduino UNO. Inventions, 6(4), 94., https://doi.org/10.3390/ inventions6040094
• Bhanage, D. A., Pawar, A. V., & Kotecha, K. (2021). IT Infrastructure Anomaly Detection and Failure Handling: A Systematic Literature Review Focusing on Datasets, Log Preprocessing, Machine & Deep Learning Approaches and Automated Tool. IEEE Access.https://doi.org/10.1109/ACCESS.2021.3128283
• Kadam, K., Ahirrao, S., Kotecha, K., & Sahu, S. (2021). Detection and localization of multiple image splicing using MobileNet V1. IEEE Access, 9, 162499-162519.. https://doi.org/10.48550/arXiv.2108.09674
• Gaikwad, M., Ahirrao, S., Phansalkar, S., & Kotecha, K. (2021). Multi-Ideology ISIS/Jihadist White Supremacist (MIWS) Dataset for Multi-Class Extremism Text Classification. Data, 6(11), 117. https://doi.org/10.5281/zenodo.5687447
• Mishra, S., Tripathy, H. K., Thakkar, H. K., Garg, D., Kotecha, K., & Pandya, S. (2021). An explainable intelligence driven query prioritization using balanced decision tree approach for multi-level psychological disorders assessment. Frontiers in Public Health, 9.https://doi.org/10.3389/fpubh.2021.795007
• Pande, J., Nasikkar, P., Kotecha, K., & Varadarajan, V. (2021). A review of maximum power point tracking algorithms for wind energy conversion systems. Journal of Marine Science and Engineering, 9(11), 1187.https://doi.org/10.3390/jmse9111187
• Sajid, M., Singh, J., Haidri, R. A., Prasad, M., Varadarajan, V., Kotecha, K., & Garg, D. (2021). A Novel Algorithm for Capacitated Vehicle Routing Problem for Smart Cities. Symmetry, 13(10), 1923..https://doi.org/10.3390/sym13101923
• Walambe, R., Marathe, A., Kotecha, K., & Ghinea, G. (2021). Lightweight object detection ensemble framework for autonomous vehicles in challenging weather conditions. Computational Intelligence and Neuroscience, 2021. https://doi.org/10.1155/2021/5278820
• Sharma, A., Kumar, V., Babbar, A., Dhawan, V., Kotecha, K., & Prakash, C. (2021). Experimental investigation and optimization of electric discharge machining process parameters using grey-fuzzy-based hybrid techniques. Materials, 14(19), 5820.. https://doi.org/10.3390/ma14195820
• Shah, A., Ahirrao, S., Pandya, S., Kotecha, K., & Rathod, S. (2021). Smart cardiac framework for an early detection of cardiac arrest condition and risk. Frontiers in Public Health, 9.. doi: https://doi.org/10.3389/fpubh.2021.762303
• Khade, S., Ahirrao, S., Phansalkar, S., Kotecha, K., Gite, S., & Thepade, S. D. (2021). Iris liveness detection for biometric authentication: A systematic literature review and future directions. Inventions, 6(4), 65. https://doi.org/10.3390/inventions6040065
• Kolekar, S., Gite, S., Pradhan, B., & Kotecha, K. (2021). Behavior Prediction of Traffic Actors for Intelligent Vehicle Using Artificial Intelligence Techniques: A Review. IEEE Access, 9, 135034-135058.doi: https://doi.org/10.1109/ACCESS.2021.3116303
• Sharma, P. K., Bhargava, C., & Kotecha, K. (2021). Sustainability analysis of a ZnO-NaCl-based capacitor using accelerated life testing and an intelligent modeling approach. Sustainability, 13(19), 10736.https://doi.org/10.3390/su131910736
• Walia, A. S., Srivastava, V., Garg, M., Somani, N., Gupta, N. K., Prakash, C., ... & Kotecha, K. (2021). Surface Roughness Analysis of H13 Steel during Electrical Discharge Machining Process Using Cu–TiC Sintered Electrode. Materials, 14(20), 5943..https://doi.org/10.3390/ma14205943
• Pandey, A., Nandgaonkar, M., Laad, M., Kotecha, K., & Kumbhar, V. (2021). Experimentation and Comparison of Engine Performance, NOx Reduction and Nano Particle Emission of Diesel, Algae, Karanja and Jatropha Oil Methyl Ester Biodiesel with CeO 2 Fuel Additive in a Military Heavy Duty 582 kW CIDI Diesel Engine (No. 2021-01-1209). SAE Technical Paper. doi: https://doi.org/10.4271/2021-01-1209
• Kadam, K. D., Ahirrao, S., & Kotecha, K. (2021). Multiple image splicing dataset (MISD): a dataset for multiple splicing. Data, 6(10), 102.https://doi.org/10.3390/data6100102
• Wagle, V., Kaur, K., Kamat, P., Patil, S., & Kotecha, K. (2021). Explainable ai for multimodal credibility analysis: Case study of online beauty health (mis)-information. IEEE Access, 9, 127985-128022. doi: https://doi.org/10.1109/ACCESS.2021.3111527.
• Singh, A., Jaiswal, V., Joshi, G., Sanjeeve, A., Gite, S., & Kotecha, K. (2021). Neural Style Transfer: A Critical Review. IEEE Access. doi: https://doi.org/10.1109/ACCESS.2021.3112996
• Kusal, S., Patil, S., Kotecha, K., Aluvalu, R., & Varadarajan, V. (2021). Ai based emotion detection for textual big data: Techniques and contribution. Big Data and Cognitive Computing, 5(3), 43.https://doi.org/10.3390/bdcc5030043
• Ruikar, K., Kotecha, K., Sandbhor, S., & Thomas, A. (2021). SPECIAL ISSUE EDITORIAL: Next Generation ICTs-How distant is ubiquitous computing?. DOI: https://www.doi.org/10.36680/j.itcon.2021.033
• Salunkhe, S., Bachute, M., Gite, S., Vyas, N., Khanna, S., Modi, K., ... & Kotecha, K. (2021). Classification of Alzheimer’s disease patients using texture analysis and machine learning. Applied System Innovation, 4(3), 49. https://doi.org/10.3390/asi4030049
• Warke, V., Kumar, S., Bongale, A., & Kotecha, K. (2021). Sustainable development of smart manufacturing driven by the digital twin framework: a statistical analysis. Sustainability, 13(18), 10139. https://doi.org/10.3390/su131810139
• Basak, A., Pramanik, A., Prakash, C., & Kotecha, K. (2021). Micro-mechanical characterization of superficial layer synthesized by electric discharge machining process. Materials Letters, 305, 130769.https://doi.org/10.1016/j.matlet.2021.130769
• Kotecha, K., Garg, D., Mishra, B., Narang, P., & Mishra, V. K. (2021). Background Invariant Faster Motion Modeling for Drone Action Recognition. Drones, 5(3), 87.https://doi.org/10.3390/drones5030087
• Shinde, R., Patil, S., Kotecha, K., & Ruikar, K. (2021). Blockchain for securing ai applications and open innovations. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 189. https://doi.org/10.3390/joitmc7030189
• Sayyad, S., Kumar, S., Bongale, A., Kamat, P., Patil, S., & Kotecha, K. (2021). Data-driven remaining useful life estimation for milling process: sensors, algorithms, datasets, and future directions. IEEE Access, 9, 110255-110286. doi:https://doi.org/10.1109/ACCESS.2021.3101284.
• Pande, S., Chouhan, S., Sonavane, R., Walambe, R., Ghinea, G., & Kotecha, K. (2021). Development and deployment of a generative model-based framework for text to photorealistic image generation. Neurocomputing, 463, 1-16.https://doi.org/10.1016/j.neucom.2021.08.055
• Walambe, R., Marathe, A., & Kotecha, K. (2021). Multiscale object detection from drone imagery using ensemble transfer learning. Drones, 5(3), 66. https://doi.org/10.3390/drones5030066
• Narkhede, P., Walambe, R., Poddar, S., & Kotecha, K. (2021). Incremental learning of LSTM framework for sensor fusion in attitude estimation. PeerJ Computer Science, 7, e662. doi:https://doi.org/10.7717/peerj-cs.662
• Patil, A. B., Bachute, M. R., & Kotecha, K. (2021). Artificial perception of the beverages: An in-depth review of the tea sample. IEEE Access, 9, 82761-82785.  Doi: https://doi.org/10.1109/ACCESS.2021.3086038
• Baviskar, D., Ahirrao, S., & Kotecha, K. (2021). Multi-Layout Invoice Document Dataset (MIDD): A Dataset for Named Entity Recognition. Data, 6(7), 78. https://doi.org/10.3390/data6070078
• Baviskar, D., Ahirrao, S., & Kotecha, K. (2021). Multi-layout Unstructured Invoice Documents Dataset: A dataset for Template-free Invoice Processing and its Evaluation using AI Approaches. IEEE Access, 9, 101494-101512. doi:  https://doi.org/10.1109/ACCESS.2021.3096739.
• Gite, S., Pradhan, B., Alamri, A., & Kotecha, K. (2021). ADMT: advanced driver’s movement tracking system using spatio-temporal interest points and maneuver anticipation using deep neural networks. IEEE Access, 9, 99312-99326. doi: https://doi.org/10.1109/ACCESS.2021.3096032.
• Gite, S., Kotecha, K., & Ghinea, G. (2021). Context–aware assistive driving: an overview of techniques for mitigating the risks of driver in real-time driving environment. International Journal of Pervasive Computing and Communications. https://doi.org/10.1108/IJPCC-11-2020-0192
• Choudrie, J., Patil, S., Kotecha, K., Matta, N., & Pappas, I. (2021). Applying and understanding an advanced, novel deep learning approach: A Covid 19, text based, emotions analysis study. Information Systems Frontiers, 23(6), 1431-1465.https://doi.org/10.1007/s10796-021-10152-6
• Baviskar, D., Ahirrao, S., Potdar, V., & Kotecha, K. (2021). Efficient automated processing of the unstructured documents using artificial intelligence: A systematic literature review and future directions. IEEE Access, 9, 72894-72936.https://doi.org/10.1109/ACCESS.2021.3072900
• Agrawal, R., Agrawal, M., Kulkarni, S., Kotecha, K., & Walambe, R. (2021). Quantitative analysis of research on artificial intelligence in retinopathy of prematurity. Libr Philos Pract, 1-29. https://digitalcommons.unl.edu/libphilprac/5342/
• Bhanage, D. A., Pawar, A. V., & Kotecha, K. (2021). Review and Analysis of Failure Detection and Prevention Techniques in IT Infrastructure Monitoring. Library Philosophy and Practice, 0_1-34.. https://digitalcommons.unl.edu/libphilprac/5248/
• Sur, A., Solke, N., Pandiya, S., & Kotecha, K. (2021, March). Design and analysis of nozzles for pneumatic windshield wiper. In IOP Conference Series: Materials Science and Engineering (Vol. 1104, No. 1, p. 012002). IOP Publishing. https://doi.org/10.1088/1757-899X/1104/1/012002
• Gaikwad, M., Ahirrao, S., Phansalkar, S., & Kotecha, K. (2021). Online extremism detection: A systematic literature review with emphasis on datasets, classification techniques, validation methods, and tools. IEEE Access, 9, 48364-48404.  doi: https://doi.org/10.1109/ACCESS.2021.3068313.
• Agrawal, R., Kulkarni, S., Walambe, R., & Kotecha, K. (2021). Assistive framework for automatic detection of all the zones in retinopathy of prematurity using deep learning. Journal of Digital Imaging, 34(4), 932-947.https://doi.org/10.1007/s10278-021-00477-8
• Joshi, G., Walambe, R., & Kotecha, K. (2021). A review on explainability in multimodal deep neural nets. IEEE Access, 9, 59800-59821.  doi: https://doi.org/10.1109/ACCESS.2021.3070212
• Mahajan, S., Hari, K. R., & Kotecha, K. (2021). A Literature Survey and Bibliometric Analysis of Application of Artificial Intelligence Techniques on Wireless Mesh Networks. Library Philosophy and Practice, 1-14.. https://digitalcommons.unl.edu/libphilprac/4937/
• Kadam, K., Ahirrao, S., & Kotecha, K. (2021). AHP validated literature review of forgery type dependent passive image forgery detection with explainable AI. International Journal of Electrical & Computer Engineering (2088-8708), 11(5). http://doi.org/10.11591/ijece.v11i5.pp4489-4501
• Karande, H., Walambe, R., Benjamin, V., Kotecha, K., & Raghu, T. S. (2021). Stance detection with BERT embeddings for credibility analysis of information on social media. PeerJ Computer Science, 7, e467.. https://doi.org/10.7717/peerj-cs.467
• Hiwale, M., Phanasalkar, S., & Kotecha, K. (2021). Using Blockchain and Distributed Machine Learning to Manage Decentralized but Trustworthy Disease Data. Science & Technology Libraries, 40(2), 190-213.. https://doi.org/10.1080/0194262X.2020.1859046

Published in 2019: 

• Sanghani, G., & Kotecha, K. (2019). Incremental personalized E-mail spam filter using novel TFDCR feature selection with dynamic feature update. Expert Systems with Applications, 115, 287-299. https://doi.org/10.1016/j.eswa.2018.07.049
• Chaudhari, P., Agrawal, H., & Kotecha, K. (2020). Data augmentation using MG-GAN for improved cancer classification on gene expression data. Soft Computing, 24(15), 11381-11391. https://doi.org/10.1007/s00500-019-04602-2
• Gite, S., Agrawal, H., & Kotecha, K. (2019). Early anticipation of driver’s maneuver in semiautonomous vehicles using deep learning. Progress in Artificial Intelligence, 8(3), 293-305. https://doi.org/10.1007/s13748-019-00177-z
• Ghayvat, H., Awais, M., Pandya, S., Ren, H., Akbarzadeh, S., Chandra Mukhopadhyay, S., ... & Chen, W. (2019). Smart aging system: uncovering the hidden wellness parameter for well-being monitoring and anomaly detection. Sensors, 19(4), 766. https://doi.org/10.3390/s19040766
• Gite, S., & Agrawal, H. (2019). Early prediction of driver's action using deep neural networks. International Journal of Information Retrieval Research (IJIRR), 9(2), 11-27. https://doi 10.4018/IJIRR.2019040102

Published Previously: 

• Pandya, S.; Ghayvat, H.; Kotecha, K.; Awais, M.; Akbarzadeh, S.; Gope, P.;Mukhopadhyay, S.C.; Chen, W., “Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring and Smart Home Security for Wellness Protocol”Applied System Innovation, volume 1, issue 4, Oct 2018. doi: https://doi.org/10.3390/asi1040042 
• P S V Nataraj K Kotecha. An improved interval global optimization algorithm using higher-order inclusion function forms, Journal of Global Optimization, vol 32, issue 1, pages, 35-63. https://doi.org/10.1007/s10898-004-5906-2
• P S V Nataraj, K Kotecha. An algorithm for global optimization using the Taylor–Bernstein form as inclusion function, Journal of Global Optimization, vol 24, issue 4, pages 417-436. doi: 10.1023/A:1021296315884
• K Kotecha, Sharnil Pandya, Anirban Sur. Influence of bed temperature on performance of silica gel/methanol adsorption refrigeration system at adsorption equilibrium using IoT and AI, Particulate Science and Technology,https://doi.org/10.1080/02726351.2020.1778145
• Ankit Thakkar and K Kotecha. Cluster Head Election for Energy and Delay Constraint Applications of Wireless Sensor Network. IEEE Sensor Journal, August 2014, Vol.14, Issue 8.  doi: 10.1109/JSEN.2014.2312549
• Priyank Thakkar and K Kotecha. Predicting Stock and Stock Price Index Movement using Trend Deterministic Data Preparation Layer , Expert system with Applications, Elsevier, Vol. 42, Issue 1, pages 259-268, doi:10.1016/j.eswa.2014.07.040
• Priyank Thakkar and K Kotecha. Predicting Stock Market Index using Fusion of Machine Learning Techniques, Expert Systems With Applications Elsevier, Vol. 42, Issue 4 March 2015, Pages 2162-2172,https://doi.org/10.1016/j.eswa.2014.10.031
• Ankit Thakkar, K Kotecha. A new Bollinger Band based energy efficient routing for clustered wireless sensor network, Applied Soft Computing, Elsevier, vol 32, pages 144-153, July 2015.https://doi.org/10.1016/j.asoc.2015.03.018
• Deshpande S, Walambe R, ‘Differential Gaming approach with safety parameter for Mobile Robot to circumvent a Dynamic Obstacle’  IFAC Journal of Elsevier https://doi.org/10.1016/j.ifacol.2020.06.080
• Sharnil Pandya, Virendra Barot, Viral Kapadia, “QoS Enabled IoT Based Low Cost Air Quality Monitoring System with Power Consumption Optimization” has been published with SCAAI affiliation in Cybernetics and Information Technologies journal, Bulgarian Academy of Science, https://doi.org/10.2478/cait-2020-0021
• Anirban Sur, Swapnil Narkhade, Ramesh Prasad Sah, Sharnil Pandya, Ketan Kotecha , “Influence of Bed Temperature on Performance of Silicagel Methanol Adsorption Refrigeration System at Adsorption Equilibrium (Smart Solar Refrigerator using IoT and AI)“, Particulate Science and Technology Journal, Taylor and Francis, https://doi.org/10.1080/02726351.2020.1778145