Publications

Published in 2023: 

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 2020: 

  • Srivastava, A., Hasan, M., Yagnik, B., Walambe, R., & Kotecha, K. (2021). Role of artificial intelligence in detection of hateful speech for Hinglish data on social media. In Applications of Artificial Intelligence and Machine Learning (pp. 83-95). Springer, Singapore. https://doi.org/10.48550/arXiv.2105.04913
  • Tiwari, S. S., Dholaria, A., Pandey, R., Nigam, G., Agrawal, R., Walambe, R., & Kotecha, K. (2020, September). Deep learning-based framework for retinal vasculature segmentation. In Congress on Intelligent Systems (pp. 275-290). Springer, Singapore. doi:: 10.1007/978-981-33-4582-9_22
  • 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. doi:10.7717/peerj-cs.348
  • Gite, S., Khatavkar, H., Kotecha, K., Srivastava, S., Maheshwari, P., & Pandey, N. (2021). Explainable stock prices prediction from financial news articles using sentiment analysis. PeerJ Computer Science, 7, e340. https://doi.org/10.7717/peerj-cs.340
  • Pandya, S., Ghayvat, H., Sur, A., Awais, M., Kotecha, K., Saxena, S., ... & Pingale, G. (2020). Pollution weather prediction system: smart outdoor pollution monitoring and prediction for healthy breathing and living. Sensors, 20(18), 5448. doi:10.3390/s20185448
  • Patil, S., Mudaliar, V. M., Kamat, P., & Gite, S. (2020). LSTM based Ensemble Network to enhance the learning of long-term dependencies in chatbot. International Journal for Simulation and Multidisciplinary Design Optimization, 11, 25., https://doi.org/10.1051/smdo/2020019
  • Apte, A., Joshi, V. A., Mehta, H., & Walambe, R. (2019). Disturbance-observer-based sensorless control of PMSM using integral state feedback controller. IEEE Transactions on Power Electronics, 35(6), 6082-6090., doi: 10.1109/TPEL.2019.2949921.
  • Sur, A., Sah, R. P., & Pandya, S. (2020). Milk storage system for remote areas using solar thermal energy and adsorption cooling. Materials Today: Proceedings, 28, 1764-1770., doi: https://doi.org/10.1016/j.matpr.2020.05.170
  • Pandya, S., Sur, A., & Kotecha, K. (2020). Smart epidemic tunnel: IoT-based sensor-fusion assistive technology for COVID-19 disinfection. International Journal of Pervasive Computing and Communications., https://doi.org/10.1108/IJPCC-07-2020-0091
  • Pandya, S., Ghayvat, H., Sur, A., Awais, M., Kotecha, K., Saxena, S., ... & Pingale, G. (2020). Pollution weather prediction system: smart outdoor pollution monitoring and prediction for healthy breathing and living. Sensors, 20(18), 5448.doi: https://www.mdpi.com/1424-8220/20/18/5448
  • Awais, M., Ghayvat, H., Krishnan Pandarathodiyil, A., Nabillah Ghani, W. M., Ramanathan, A., Pandya, S., ... & Faye, I. (2020). Healthcare professional in the loop (HPIL): classification of standard and oral cancer-causing anomalous regions of oral cavity using textural analysis technique in autofluorescence imaging. Sensors, 20(20), 5780. https://doi.org/10.3390/s20205780
  • Patel, C. I., Labana, D., Pandya, S., Modi, K., Ghayvat, H., & Awais, M. (2020). Histogram of oriented gradient-based fusion of features for human action recognition in action video sequences. Sensors, 20(24), 7299. doi:10.3390/s20247299
  • Gite, S., Khatavkar, H., Kotecha, K., Srivastava, S., Maheshwari, P., & Pandey, N. (2021). Explainable stock prices prediction from financial news articles using sentiment analysis. PeerJ Computer Science, 7, e340.. https://doi.org/10.7717/peerj-cs.340
  • Deshpande, N. M., Gite, S. S., & Aluvalu, R. (2020). A brief bibliometric survey of leukemia detection by machine learning and deep learning approaches. Lib. Philo. Pract, 4569. https://digitalcommons.unl.edu/libphilprac/4569

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

Patents :

  1. PCT patent entitled ‘A SYSTEM AND A METHOD FOR DETECTION AND CLASSIFICATION OF GASSES’ published in September 2019 (PCT/IB2019/055905 as WO/2019/171363A2 - 13.09.2019)
  2. Indian Patent Application No. IN201921018281 entitled ‘A SYSTEM AND A METHOD FOR DETECTION AND CLASSIFICATION OF GASSES’ published in Sept 2019.
  3. PCT Patent Entitled ' A Feedback based Assistive System and Method for visually Impaired Persons’ published in October 2019 (PCT/IB2019/056833  as WO/2019/198064 on 17.10.2019)
  4. Indian Patent Application No. IN201921027908 entitled ‘A Feedback based Assistive System and Method for Visually Impaired Persons’ published in Sept 2019.
about scri

Symbiosis Centre For Research and Innovation (SCRI), established in 2009, is the dedicated department of Symbiosis International (Deemed University) for promoting and facilitating research among students and faculty. Through its academic and administrative services, SCRI enables researchers to achieve excellence in their work, and eventually, translates SIU's vision of creation of knowledge for the benefit of the Society into reality.