Text/Edited Books
| 2. | Bhabesh Deka, P. Maji, S. Mitra, D. K. Bhattacharyya, P. K. Bora, and S. K. Pal (Eds.), “Pattern Recognition and Machine Intelligence”, Lecture Notes in Computer Science (LNCS) book series, Springer, vol. 11941 and 11942, 2019. |
| 1. | Bhabesh Deka and Sumit Datta, “Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms- A Convex Optimization Approach”, Springer Series on Bio- and Neurosystems, Springer Singapore, 2019, DOI: 10.1007/978-981-13-3597-6 |
Selected Journal Publications (2013-present):
| 25. | Bhabesh Deka and Debarun Chakraborty UAV Sensing-based Litchi Segmentation using Modified Mask-RCNN for Precision Agriculture , IEEE Transactions on Agrifood Electronics , 2024. |
| 26. | Rahul Sharma, Bhabesh Deka , Vincent Fusco, and Okan Yurduseven Integrated convolutional neural networks for joint super-resolution and classification of radar images , Pattern Recognition, Elsevier , 2024. (SCI, JCR IF = 8) |
| 25. | Trishna Barman and Bhabesh Deka A Deep Learning-based Joint Image Super-resolution and Deblurring Framework , IEEE Transactions on Artificial Intelligence , 2024. (CiteScore 4.9) |
| 24. | Bhabesh Deka and Dipen Deka Nonlinear analysis of heart rate variability signals in meditative state: a review and perspective , BioMedical Engineering OnLine, 22 (35) , 2023. (SCIE, JCR IF = 3.9) |
| 23. | Dipen Deka and Bhabesh Deka Detection of Meditation-Induced HRV Dynamics using Averaging Technique-based Oversampled Feature set and machine learning classifiers , IEEE Access, 2023. (SCI, JCR IF = 3.367) |
| 22. | Trishna Barman, Bhabesh Deka , and Helal Uddin Mullah Edge Preserving Single Remote Sensing Image Super-resolution using Sparse Representations, SN Computer Science, Springer , 2023. (Scopus and UGC-CARE Indexed) |
| 21. | Bhabesh Deka , Helal Uddin Mullah, Trishna Barman, and Sumit Datta Joint Sparse Representation-based Single Image Super-Resolution for Remote Sensing Applications , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023. (SCI, JCR IF = 4.715) |
| 20. | Rahul Sharma, Jiaming Zhang, Rupesh Kumar, Bhabesh Deka , Vincent Fusco, and Okan Yurduseven 3D Super-Resolution of Coded Aperture Millimeter-wave Images using Complex-Valued Convolutional Neural Network, IEEE Sensors Journal, 2022. (SCI, JCR IF = 4.325) |
| 19. | Bhabesh Deka, Sushant Kumar and Sumit Datta, Dictionary Learning-based Multi-Channel ECG Reconstruction using Compressive Sensing, IEEE Sensors Journal, 2022. (SCI, JCR IF = 4.325) |
| 18. | Bhabesh Deka and Dipen Deka, An Improved Multiscale Distribution Entropy for Analyzing Complexity of Real-World Signals, Chaos, Solitons and Fractals: the interdisciplinary journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena (Elsevier), 2022.(SCI, JCR IF = 7.8) |
| 17. | Rahul Sharma, Raphael Hussung, Andreas Keil,Fabian Friederich, Thomas Fromenteze, Mohsen Khalily, Bhabesh Deka, Vincent F. Fusco and Okan Yurduseven, Coded-Aperture Computational Millimeter-wave Image Classifier using Convolutional Neural Network, IEEE Access, 2021.(SCI, JCR IF = 3.476) |
| 16. | Sumit Datta, Samarendra Dandapat and Bhabesh Deka, A Deep Framework for Enhancement of Diagnostic Information in CSMRI Reconstruction, Biomedical Signal Processing and Control (Elsevier), 2021.(SCI, JCR IF = 5.076) |
| 15. | Dipen Deka and Bhabesh Deka, Stratification of High-Risk Hypertensive Patients using Hybrid Heart Rate Variability Features and Boosting Algorithms, IEEE Access, vol. 9, pp. 62665-62675, 2021.(SCI, JCR IF = 3.476) |
| 14. | Rahul Sharma, Okan Yurduseven, Bhabesh Deka, and Vincent Fusco, Hardware Enabled Acceleration of Near-Field Coded Aperture Radar Physical Model for Millimetre-Wave Computational Imaging , Progress In Electromagnetics Research B (PIER), vol. 90, pp. 91-108, 2021.(Scopus) |
| 13. | Dipen Deka, Bhabesh Deka, Characterization of heart rate variability signal for distinction of meditative and pre-meditative states , Biomedical Signal Processing and Control (Elsevier), vol. 66, 2021.(SCI, JCR IF = 5.076) |
| 12. | Bhabesh Deka, Helal Uddin Mullah, Sumit Datta, Vijaya Lakshmi, and Rajarajeswari Ganesan, Sparse Representation Based Super-Resolution of MRI Images with Non-Local Total Variation Regularization, SN Computer Science, Springer, vol. 1, pp. 1-13, 2020.(Scopus and UGC-CARE Indexed) |
| 11. | Sushant Kumar, Bhabesh Deka, and Sumit Datta, Multichannel ECG Compression using Block Sparsity based Joint Compressive Sensing, Circuits, Systems and Signal Processing, Springer, vol. 39, pp. 6299-6315, 2020. (SCI, JCR IF = 2.311) |
| 10. | Bhabesh Deka, Sumit Datta, Helal Uddin Mullah and Suman Hazarika, Diffusion-weighted and Spectroscopic MRI Super-resolution using Sparse Representations, Biomedical Signal Processing and Control (Elsevier), vol. 60, 2020. (SCI, JCR IF = 5.076) |
| 9. | Helal Uddin Mullah, Bhabesh Deka and A V V Prasad, Fast Multispectral Image Super-resolution via Sparse Representation, IET Image Processing (IET), vol. 14, pp. 2833-2844, 2020. (SCI, JCR IF = 1.773) |
| 8. | Bhabesh Deka and Sumit Datta, Calibrationless Joint Compressed Sensing Reconstruction for Rapid Parallel MRI, Biomedical Signal Processing and Control (Elsevier), vol. 58, 2020. (SCI, JCR IF = 5.076) |
| 7. | Bhabesh Deka, Sparse representations and compressive sensing in multi-dimensional signal processing, CSI Transactions on ICT, Springer, pp. 1-10, 2019. |
| 6. | Sumit Datta and Bhabesh Deka, An Efficient Interpolated Compressed Sensing Reconstruction Scheme for 3D MRI, IET Image Processing (IET), vol. 12, no. 11, pp. 2119-2127, 2018. (SCI, JCR IF = 1.773) |
| 5. | Bhabesh Deka, Sumit Datta, and Sanjeev Handique, Wavelet Tree Support Detection for Compressed Sensing MRI Reconstruction, IEEE Signal Processing Letters, vol. 25, no. 5, pp. 730-734, 2018. (SCI, JCR IF = 3.201) |
| 4. | Sumit Datta and Bhabesh Deka, Magnetic Resonance Image Reconstruction using Fast Interpolated Compressed Sensing, Journal of Optics (India), Springer, vol. 47, no. 2, pp. 154-165, 2017. (ESCI, Scopus, UGC-CARE) |
| 3. | Bhabesh Deka , M. Handique and Sumit Datta, Sparse Regularization Method for the Detection and Removal of Random-Valued Impulse noise, Multimedia Tools and Applications, Springer, vol. 76, no. 5, pp. 6355–6388, 2016. (SCI, JCR IF = 2.577) |
| 2. | Bhabesh Deka and P. K. Bora, Removal of Correlated Speckle Noise Using Sparse and Overcomplete Representations, Biomedical Signal Processing and Control (Elsevier), vol. 8, no. 6, pp. 520-533, 2013. (SCI, JCR IF = 5.076) |
| 1. | Bhabesh Deka and P. K. Bora, Wavelet Based Despeckling of Medical Ultrasound Images, IETE Journal of Research (Taylor and Francis), vol. 59, no. 2, 2013. (SCI, JCR IF = 1.877) |
Book Chapters:
| 13. | Debarun Chakraborty and Bhabesh Deka, “Litchi Fruit Instance Segmentation from UAV Sensed Images Using Spatial Attention-Based Deep Learning Model”, In: Maji, P., Huang, T., Pal, N.R., Chaudhury, S., De, R.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2023. Lecture Notes in Computer Science, vol 14301, Springer, Cham., 2023. |
| 12. | Dipen Deka, Bhabesh Deka, “Investigation on HRV Signal Dynamics for Meditative Intervention”, Soft Computing: Theories and Applications, Springer,, pp. 993-1005, 2020. |
| 11. | Sushant Kumar, Bhabesh Deka and Sumit Datta, “Multi-channel ECG Reconstruction based on Joint Compressed Sensing for Healthcare Applications”, Compressed Sensing in Healthcare (Academic Press), Elsevier, pp. 185-200, 2020. |
| 10. | Sumit Datta and Bhabesh Deka, “Calibrationless Parallel Compressed Sensing Reconstruction for Rapid Magnetic Resonance Imaging”, Compressed Sensing in Healthcare (Academic Press), Elsevier, pp. 269-281, 2020. |
| 9. | S. Kumar, Bhabesh Deka, and S. Datta, “Block-Sparsity Based Compressed Sensing for Multichannel ECG Reconstruction”, Pattern Recognition and Machine Intelligence, LNCS, Springer, vol. 11942, pp. 210-217, 2019. |
| 8. | Bhabesh Deka, H. U. Mullah, S. Datta, V. Lakshmi, and R. Ganesan, “Sparse Representation Based Super-Resolution of MRI Images with Non-Local Total Variation Regularization”, Pattern Recognition and Machine Intelligence, LNCS, Springer, vol. 11942, pp. 78-86, 2019. |
| 7. | S. Datta and Bhabesh Deka, “Group-Sparsity Based Compressed Sensing Reconstruction for Fast Parallel MRI”, Pattern Recognition and Machine Intelligence, LNCS, Springer, vol. 11942, pp. 70-77, 2019. |
| 6. | H. U. Mullah, Bhabesh Deka, T. Barman, and A. V. V. Prasad, “Sparsity Regularization Based Spatial-Spectral Super-Resolution of Multi spectral Imagery”, Pattern Recognition and Machine Intelligence, LNCS, Springer, vol. 11941, pp. 523-531, 2019. |
| 5. | Sumit Datta and Bhabesh Deka, “Multi-channel, Multi-slice, and Multi-contrast Compressed Sensing MRI Using Weighted Forest Sparsity and Joint TV Regularization Priors”, Soft Computing for Problem Solving (SoCProS 2017), Advances in Intelligent Systems and Computing, Springer, 2018. |
| 4. | H. U. Mullah and Bhabesh Deka, “A Fast Satellite Image Super-Resolution Technique Using Multicore Processing”, Hybrid Intelligent Systems (HIS 2017), Advances in Intelligent Systems and Computing, Springer, vol. 734, pp. 51--60, 2018. |
| 3. | Bhabesh Deka and Sumit Datta, “Weighted Wavelet Tree Sparsity Regularization for Compressed Sensing Magnetic Resonance Image Reconstruction”, Advances in Electronics, Communication and Computing (ETAEERE 2016), Lecture Notes in Electrical Engineering, Springer, vol. 443, pp. 449--457, 2016. |
| 2. | Mayuri Kalita and Bhabesh Deka, “Random-valued Impulse Denoising using a Fast L1-Minimization based Image Inpainting Technique”, Advances in Electronics, Communication and Computing (ETAEERE 2016), Lecture Notes in Electrical Engineering, Springer, vol. 443, pp. 633--641, 2016. |
| 1. | Bhabesh Deka, and S. Datta, “A Practical Under-Sampling Pattern for Compressed Sensing MRI”, Advances in Communication and Computing, Lecture Notes in Electrical Engineering, Springer, vol. 347, pp. 115--125, 2015. |
International and National Conferences:
| 32. | Rahul Sharma, Jiaming Zhang, Rupesh Kumar, Bhabesh Deka, Vincent Fusco, and Okan Yurduseven, “Super-Resolution Reconstruction and Denoising of 3D Millimetre-Wave Images Using a Complex-Valued Convolutional Neural Network”, 17th European Conference on Antennas and Propagation (EuCAP), Florence, Italy, pp. 1-5, 2023. |
| 31. | Rahul Sharma, Rupesh Kumar, Bhabesh Deka, Vincent Fusco, and Okan Yurduseven, “Effect of Magnitude and Phase of Millimeter-Wave Images on Classification Accuracy”, 17th European Conference on Antennas and Propagation (EuCAP), Florence, Italy, pp. 1-4, 2023. |
| 30. | Trishna Barman and Bhabesh Deka, “Attention-based Residual Network for Single Image Remote Sensing Super-resolution”, 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) , Greater Noida, India, pp. 569-574, 2022. |
| 29. | Sumit Datta, Bhabesh Deka, Samarendra Dandapat, Sushant Kumar and Arnab Majumder, “Enhancement of Diagnostic Information in T1-weighted Contrast Enhanced MRI using Deep Back-Projection based Super-Resolution”, IEEE 19th India Council International Conference (INDICON), Kerala, India, 2022. |
| 28. | Rahul Sharma, Raphael Hussung, Andreas Keil, Fabian Friederich, Thomas Fromenteze, Mohsen Khalily, Bhabesh Deka, Vincent Fusco, and Okan Yurduseven, “Performance Analysis of Classification Algorithms for Millimeter-Wave Imaging”, European Conference on Antennas and Propagation, Madrid, Spain, 2022. |
| 27. | Trishna Barman, Bhabesh Deka, and AVV Prasad, “GPU-accelerated adaptive dictionary learning and sparse representations for multispectral image super-resolution” , IEEE 18th India Council International Conference (INDICON), Guwahati, 2021. |
| 26. | Dipen Deka and Bhabesh Deka, “A Decision Support System for Prediction of Paroxysmal Atrial Fibrillation based on Heart Rate Variability Metrics” , IEEE 18th India Council International Conference (INDICON), Guwahati, 2021. |
| 25. | Rahul Sharma, The Viet Huang, Bhabesh Deka, Vincent Fusco, and Okan Yurduseven, “Towards a convolutional neural network coupled millimetre-wave coded aperture image classifier system”, Proc. SPIE 11745, Passive and Active Millimeter-Wave Imaging XXIV, 117450C (12 April 2021). |
| 24. | Sumit Datta, Samarendra Dandapat and Bhabesh Deka, “A Novel Framework for Enhancement of Diagnostic Information in MRI using Deep Super-Resolution”, 2020 IEEE Applied Signal Processing Conference (ASPCON), pp. 94-98, 2020. |
| 23. | Sumit Datta, Vineeta Das, Samarendra Dandapat and Bhabesh Deka, “A Novel Framework for Enhancement of Diagnostic Information in MR Imaging using Super-Resolution”, IEEE International Conference on Advanced Communication Technologies and Signal Processing, 2020. |
| 22. | Dipen Deka, Bhabesh Deka, “Computer-aided Detection of Congestive Heart Failure based on Nonlinear HRV Features”, IEEE International Conference on Machine Learning & Applied Network Technologies, 2020. |
| 21. | Sushant Kumar, Bhabesh Deka and S. Datta, “Weighted Block CS for Multichannel Fetal ECG Reconstruction”, TENCON 2019-IEEE Region 10 Conference, pp. 2324-2328, 2019. |
| 20. | Helal Uddin Mullah and Bhabesh Deka, “Parallel Multispectral Image Super-resolution Based on Sparse Representations”, 2nd International Conference on Innovations in Electronics, Signal Processing and Communication (IESC), 2019. |
| 19. | Sumit Datta and Bhabesh Deka, “ Interpolated Compressed Sensing for Calibrationless Parallel MRI Reconstruction”, 25 National Conference on Communications (NCC) , Bangalore, India, 2019. |
| 18. | Sumit Datta and Bhabesh Deka, “Efficient Adaptive Weighted Minimization for Compressed Sensing Magnetic Resonance Image Reconstruction”, Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2016. |
| 17. | Sumit Datta, Bhabesh Deka, Helal Uddin Mullah and Sushant Kumar, “An Efficient Interpolated Compressed Sensing Method for Highly Correlated 2D Multi-slice MRI”, International Conference on Accessibility to Digital World (ICADW), 2016. |
| 16. | Sumit Datta and Bhabesh Deka, “Magnetic Resonance Image Reconstruction using Fast Interpolated Compressed Sensing”, International Conference on Light and Light based Technologies (ICLLT), 2016. |
| 15. | Bhabesh Deka , M. Handique and S. Datta, “Random-Valued Impulse Denoising usingSparse Regularizations”, Proc. of ICIIP 2015, 2015. |
| 14. | S. Datta, S. Kalita, U. Bhattacharyya, Bhabesh Deka, “A simple machine vision technique to asses quality of rice grains”, Proc. of National Seminar Cum Workshop on Innovative Prospects in Food processing: Integration of Engineering and Biological Science , 2015. |
| 13. | Bhabesh Deka and S. Datta, “High Throughput MR Image Reconstruction using Compressive Sensing”, Proc. of ICVGIP 2014 , 2014. |
| 12. | Bhabesh Deka, K.Gorain, N. Kalita, and B. Das, “Single Image Super-Resolution Using Compressive Sensing with Learned Overcomplete Dictionary”, Proc. of IEEE sponsored NCVPRIPG , 2013. |
| 11. | Bhabesh Deka and D. Baishnab, “Removal of Random-valued Impulse Noise Using Overcomplete DCT Dictionary”, Proc. of International Information Technology Conference and Exhibition (CUBE 2012), 2012. |
| 10. | Bhabesh Deka, P. K. Bora, “A Noncausal Linear Prediction Based Switching Median Filter for the Removal of Salt and Pepper Noise”, Proc. of IEEE International Conference on Signal Processing and Communications (SPCOM 2012), IISC Bangalore, 2012. |
| 9. | Bhabesh Deka and D. Baishnab, “A Linear Prediction Based Switching Median Filter for the Removal of Salt and Pepper Noise from Highly Corrupted Image”, Proc. IEEE sponsored Conference on Computational Intelligence and Signal Processing (CISP2012), 2012. |
| 8. | Bhabesh Deka and P. K. Bora, “Removal of Random Valued Impulse Noise Using Sparse Representation”, Proc. of IEEE National Conference on Communications (NCC), 2011. |
| 7. | Bhabesh Deka and P. K. Bora, “Enhancing the Performance of the Bayesian Pursuit Algorithm”, Proc. of IEEE National Conference on Communications (NCC), 2011. |
| 6. | Bhabesh Deka and P. K. Bora, “Despeckling of Medical Ultrasound Images Using Sparse Representation”, Proc. of IEEE International Conference of Signal Processing and Communications (SPCOM), 2010. |
| 5. | Bhabesh Deka and P.K. Bora, “A Versatile Statistical Model for Despeckling of Medical Ultrasound Images”, Proc. of IEEE INDICON , 2009. |
| 4. | A. Talukdar, Bhabesh Deka, and P. K. Bora, “Wavelet Based Adaptive Bayesian Despeckling for Medical Ultrasound Images”, Proc. of IEEE TENCON-2009, 2009. |
| 3. | Bhabesh Deka, “Medical Ultrasound Image Denoising”, proceedings of seminar on Bioelectronics (as a part of dissemination of innovative programme "Bioelectronics"), Tezpur University , 2007. |
| 2. | Bhabesh Deka and D. Ghosh, “Watershed segmentation for medical ultrasound images”, IEEE International Conference on Systems, Man, and Cybernetics, pp. 3186-3191, 2006. |
| 1. | Bhabesh Deka and D. Ghosh, “Ultrasound image segmentation using watersheds and region merging”, IET International Conference on Visual Information Engineering, pp. 110-115, 2006. |