Research Work

1. N. A. Choudhury and B. Soni, "Enhanced Complex Human Activity Recognition System: A Proficient Deep Learning Framework Exploiting Physiological Sensors and Feature Learning," in IEEE Sensors Letters, doi: 10.1109/LSENS.2023.3326126. (2023)  [IF - 2.8]

2. N. A. Choudhury and B. Soni, "An Efficient and Lightweight Deep Learning Model for Human Activity Recognition on Raw Sensor Data in Uncontrolled Environment," in IEEE Sensors Journal, doi: 10.1109/JSEN.2023.3312478. (2023)  [IF - 4.3]

3. N. A. Choudhury, B. Soni, "In-depth analysis of design & development for sensor-based human activity recognition system" in Multimedia Tools Applications (2023). https://doi.org/10.1007/s11042-023-16423-5 (2023). [IF - 3.6]

4. N. A. Choudhury and B. Soni, "An Adaptive Batch Size-Based-CNN-LSTM Framework for Human Activity Recognition in Uncontrolled Environment," in IEEE Transactions on Industrial Informatics, vol. 19, no. 10, pp. 10379-10387, Oct. 2023, doi: 10.1109/TII.2022.3229522. [IF- 12.3]  My Best Journal Paper 😅.

5. N. A. Choudhury, S. Moulik and D. S. Roy, "Physique-Based Human Activity Recognition Using Ensemble Learning and Smartphone Sensors," in IEEE Sensors Journal, vol. 21, no. 15, pp. 16852-16860, 1 Aug.1, 2021, doi: 10.1109/JSEN.2021.3077563. [IF  4.3] - My First Journal Paper 😊.

Revision & Under Review - 

5. 1. N. A. Choudhury and B. Soni, “KNEE-HAR: A ConvLSTM-based Lightweight Hybrid Deep Learning Model for Human Activity Recognition with Knee Abnormalities using Raw Physiological Sensors Data,” in EEE Sensors Journal – Major Revision on 08-05-2024.

5. 2. N. A. Choudhury, B. Soni, S. Moulik, “A Novel Semi-supervised Hybrid Deep Learning-assisted Automatic Feature Engineering Framework for Human Activity Recognition   System”, IEEE Transactions on Industrial Informatics.  – Under Review Since 01-04-2024.

5. 3. N. A. Choudhury and B. Soni, “Towards Optimal Data Acquisition Modules for Smartphone Sensor-based Human Activity Recognition Systems in Ubiquitous Environment,” in Elsevier Engineering Applications of Artificial Intelligence – Under Review Since 01-02-2024.

5. 4. N. A. Choudhury, S. Singh and B. Soni, “An Efficient Ensemble Framework for Human Gait Recognition using CNN-LSTM with Extra Tree Classifier and Smartphone   Sensors in Real-World Environment”, in IEEE Sensors Letters. – (Under Review Since 22-04-2024) 

1. N. A. Choudhury and B. Soni, "Human Activity Recognition: In-Depth Design Analysis with New Tools and Techniques  ", in Springer Book Series - Proposal Accepted (Authored Book)

2. N. A. Choudhury and B. Soni, "A Lightweight and Efficient Hybrid Deep Learning Framework for Multi-Resident Activity Recognition in Real-World Environment ", in IET Special Call - Multi resident Activity Recognition using Deep Learning Models - Accepted (Book Chapter)

1. N. A. Choudhury, S. Moulik and S. Choudhury, "Cloud-based Real-time and Remote Human Activity Recognition System using Wearable Sensors," 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), Taoyuan, Taiwan, 2020, pp. 1-2, doi: 10.1109/ICCE-Taiwan49838.2020.9258050. (2nd Position in Best Demo Paper Award) ONLINE

2.  S. Rajesh, N. A. Choudhury and S. Moulik, "Hepatocellular Carcinoma (HCC) Liver Cancer prediction using Machine Learning Algorithms," 2020 IEEE 17th India Council International Conference (INDICON), New Delhi, India, 2020, pp. 1-5, doi: 10.1109/INDICON49873.2020.9342443. ONLINE

3.  I. A. Marbaniang, N. A. Choudhury and S. Moulik, "Cardiovascular Disease (CVD) Prediction using Machine Learning Algorithms," 2020 IEEE 17th India Council International Conference (INDICON), New Delhi, India, 2020, pp. 1-6, doi: 10.1109/INDICON49873.2020.9342297. ONLINE

4.  A. C. Lyngdoh, N. A. Choudhury and S. Moulik, "Diabetes Disease Prediction Using Machine Learning Algorithms," 2020 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), Langkawi Island, Malaysia, 2021, pp. 517-521, doi: 10.1109/IECBES48179.2021.9398759. ONLINE

5. N. A. Choudhury and B. Soni, "Effect of Shallow and Ensemble Learning Models for Human Activity Recognition in Uncontrolled Environment," 2022 IEEE 19th India Council International Conference (INDICON), Kochi, India, 2022, pp. 1-6, doi: 10.1109/INDICON56171.2022.10039755. (PhD Work - 2022) ONLINE

6. N. A. Choudhury and B. Soni, "An Efficient CNN-LSTM Approach for Smartphone Sensor-Based Human Activity Recognition System," 2022 5th International Conference on Computational Intelligence and Networks (CINE), Bhubaneswar, India, 2022, pp. 01-06, doi: 10.1109/CINE56307.2022.10037495.  (PhD Work-2022) ONLINE

7. S. Singh, N. A. Choudhury and B. Soni, "Gait Recognition Using Activities of Daily Livings and Ensemble Learning Models" In: Mishra, A., Gupta, D., Chetty, G. (eds) Advances in IoT and Security with Computational Intelligence. ICAISA 2023. Lecture Notes in Networks and Systems, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-99-5085-0_20. ONLINE 

8. B. Deb, N. A. Choudhury and B. Soni, "Effect of Shallow Learning Techniques and Feature Selection for Breast Cancer Detection." In: Gabbouj, M., Pandey, S.S., Garg, H.K., Hazra, R. (eds) Emerging Electronics and Automation. E2A 2022. Lecture Notes in Electrical Engineering, vol 1088. Springer, Singapore. ONLINE

9. K. Barbhuiya, S. Kumar, T. Kalita, N. A. Choudhury and B. Soni, "An Efficient Hybrid Deep Learning-based Automatic Feature Engineering and Classification Framework for Smartphone Sensor-based Human Activity Recognition System", in 8th Students' Conference on Engineering & Systems (SCES-2024), India, 2024, (Accepted)

10. M.Ruperi, Dinesh, Neha, N. A. Choudhury and B. Soni, "An Efficient and Optimized CNN-LSTM Framework for Complex Human Activity Recognition System using Surface EMG Physiological Sensors and Feature Engineering", in 8th Students' Conference on Engineering & Systems (SCES-2024), India, 2024, (Accepted)