Book Chapters (29)

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2026 (7)

1. Luharuka, I., Varshney, A., Sarkar, S., & Bose, I. (2026). V-SVM: A VGG19-based Support Vector Machine for Early Detection of Parkinson's Disease. In: Maiti, J., Rai, R.N., Menon, B.G., Ahuja, R., Shrigondekar, H.H. (eds) Safety, Health, and Analytics-Driven Governance Toward Sustainable Development. SHADG 2024. Lecture Notes in Mechanical Engineering. pp 169–177. Springer, Singapore. (Link: Paper)

2. Kumar, A., Amrita, & Sarkar, S. (2026). Social media sentiment analysis of impacts of COVID-19 on mothers and children. In: Operations research and data analytics: Current trends and future perspectives (Lecture Notes on Multidisciplinary Industrial Engineering), (p. 139–155). Springer. (Link: Paper)

3. Varshney, A., Luharuka, I., Sarkar, S., & Bose, I. (2026). Alzheimer's Disease Detection using Gaussian-Based Bayesian Parameter Optimization-based Deep Convolution Neural Network. In Operations Research and Data Analytics: Current Trends and Future Perspectives. Lecture Notes on Multidisciplinary Industrial Engineering. (p. 157–175). Springer, Singapore. (Link: Paper)

4. Srivastava, A., Sarkar, S., & Bose, I. (2026). Toward Early Parkinson's Disease Detection: A Novel RL-CNN Based Approach. In Operations Research and Data Analytics: Current Trends and Future Perspectives. Lecture Notes on Multidisciplinary Industrial Engineering. (p. 177–193). Springer, Singapore. (Link: Paper)

5. Tulsyan, P., Ghosh, A., & Sarkar, S. (2026). Eye-Tracking-Based Packaging Analysis for Toy Industry Using Bayesian Belief Networks and Evidential Reasoning Approach. In Recent Advances in Industrial and Systems Engineering. Lecture Notes on Multidisciplinary Industrial Engineering. (p. 103–121) Springer, Singapore. (Link: Paper)

6. Sarker, S., Pramanik, A., Sarkar, S., & Bose, I.  (2026). OptiTrackEx: A Deep Learning Approach to Real Time Vehicle Collision. In Proceedings of the 13th Asia Pacific Conference on Transportation and the Environment (APTE) 2024. APTE 2024. Lecture Notes in Civil Engineering, vol 722. (p. 445-455). Springer, Singapore. (Link: Paper)

7. Sarker, S., Pramanik, A., & Sarkar, S. (2026). A Two-Stage Method for Detection and Distance Perception of Traffic Lights. In Proceedings of the 13th Asia Pacific Conference on Transportation and the Environment (APTE) 2024. Lecture Notes in Civil Engineering, vol 722.  (pp 457–466). Springer, Singapore. (Link: Paper)

2025 (1)

1. Srivastava, Apurb, Sarkar, S., & Djeddi, C. (2025). Soil Fertility Detection using Reinforcement Learning-based Recurrent Neural Network. In: García Márquez, F.P., Hameed, A.A., Jamil, A. (eds) Pattern Recognition and Artificial Intelligence. Lecture Notes in Networks and Systems, vol 1393. Springer, Cham. (Link: Paper)

2022 (5)

1. Pramanik, A., Sarkar, S., Djeddi, C., & Maiti, J. (2022). Real-Time Detection of Traffic Anomalies Near Roundabouts. In Mediterranean Conference on Pattern Recognition and Artificial Intelligence (pp. 253-264). Springer, Cham. (Link: Paper)

2. Maity, S., Rastogi, A., Djeddi, C., Sarkar, S., & Maiti, J. (2022). A Novel Optimized Method for Feature Selection Using Non-linear Kernel-Free Twin Quadratic Surface Support Vector Machine. In Mediterranean Conference on Pattern Recognition and Artificial Intelligence (pp. 339-353). Springer, Cham. (Link: Paper)

3. Kosuri, M., Tandu, C., Sarkar, S., & Maiti, J. (2022). Multivariate Deep Learning Model with Ensemble Pruning for Time Series Forecasting. In Proceedings of the Seventh International Conference on Mathematics and Computing (pp. 321-334). Springer, Singapore. (Link: Paper)

4. Rao, A., Sarkar, S., Pramanik, A., & Maiti, J. (2022). Predicting and Analysing Pedestrian Injury Severity: A Machine Learning-Based Approach. In Proceedings of the Seventh International Conference on Mathematics and Computing (pp. 485-497). Springer, Singapore. (Link: Paper)

5. Tandu, C., Kosuri, M., Sarkar, S., & Maiti, J. (2022). A Two-Fold Multi-objective Multi-verse Optimization-Based Time Series Forecasting. In Proceedings of the Seventh International Conference on Mathematics and Computing (pp. 743-754). Springer, Singapore. (Link: Paper)

2019 (2)

1. Sarkar, S., Chain, M., Nayak, S., & Maiti, J. (2019). Decision support system for prediction of occupational accident: a case study from a steel plant. In Emerging Technologies in Data Mining and Information Security (pp. 787-796). Springer, Singapore. (Link: Paper)

2. Pramanik, A., Sarkar, S., & Maiti, J. (2019). Oil spill detection using image processing technique: An occupational safety perspective of a steel plant. In Emerging Technologies in Data Mining and Information Security (pp. 247-257). Springer, Singapore. (Link: Paper)

2018 (2)

1. Verma, A., Chatterjee, S., Sarkar, S., & Maiti, J. (2018). Data-driven mapping between proactive and reactive measures of occupational safety performance. In Industrial Safety Management (pp. 53-63). Springer, Singapore. (Link: Paper)

2. Sarkar, S., Verma, A., & Maiti, J. (2018). Prediction of occupational incidents using proactive and reactive data: a data mining approach. In Industrial Safety Management (pp. 65-79). Springer, Singapore.  (Link: Paper)

2017 (2)

1. Sarkar, S., Lohani, A., & Maiti, J. (2017). Genetic algorithm-based association rule mining approach towards rule generation of occupational accidents. In International Conference on Computational Intelligence, Communications, and Business Analytics (pp. 517-530). Springer, Singapore. (Link: Paper)

2. Sarkar, S., Lakha, V., Ansari, I., & Maiti, J. (2017). Supplier selection in uncertain environment: a fuzzy MCDM approach. In Proceedings of the First International Conference on Intelligent Computing and Communication (pp. 257-266). Springer, Singapore. (Link: Paper)