| Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms B Deka, S Datta Springer series on bio-and neurosystems, 2019 | 22 | 2019 |
| Wavelet tree support detection for compressed sensing MRI reconstruction B Deka, S Datta, S Handique IEEE Signal Processing Letters 25 (5), 730-734, 2018 | 22 | 2018 |
| Sparse regularization method for the detection and removal of random-valued impulse noise B Deka, M Handique, S Datta Multimedia Tools and Applications 76, 6355-6388, 2017 | 18 | 2017 |
| Efficient interpolated compressed sensing reconstruction scheme for 3D MRI S Datta, B Deka IET Image Processing 12 (11), 2119-2127, 2018 | 16 | 2018 |
| Magnetic resonance image reconstruction using fast interpolated compressed sensing S Datta, B Deka Journal of Optics 47, 154-165, 2018 | 16 | 2018 |
| Multichannel ECG compression using Block-Sparsity-based joint compressive sensing S Kumar, B Deka, S Datta Circuits, Systems, and Signal Processing 39 (12), 6299-6315, 2020 | 14 | 2020 |
| Calibrationless joint compressed sensing reconstruction for rapid parallel MRI B Deka, S Datta Biomedical Signal Processing and Control 58, 101871, 2020 | 13 | 2020 |
| An efficient interpolated compressed sensing method for highly correlated 2D multi-slice MRI S Datta, B Deka, HU Mullah, S Kumar 2016 International Conference on Accessibility to Digital World (ICADW), 187-192, 2016 | 11 | 2016 |
| Multi-channel, multi-slice, and multi-contrast compressed sensing MRI using weighted forest sparsity and joint TV regularization priors S Datta, B Deka Soft Computing for Problem Solving: SocProS 2017, Volume 1, 821-832, 2019 | 9 | 2019 |
| A practical under-sampling pattern for compressed sensing MRI B Deka, S Datta Advances in Communication and Computing, 115-125, 2015 | 8 | 2015 |
| Diffusion-weighted and spectroscopic MRI super-resolution using sparse representations B Deka, S Datta, HU Mullah, S Hazarika Biomedical Signal Processing and Control 60, 101941, 2020 | 7 | 2020 |
| Weighted wavelet tree sparsity regularization for compressed sensing magnetic resonance image reconstruction B Deka, S Datta Advances in Electronics, Communication and Computing: ETAEERE-2016, 449-457, 2018 | 7 | 2018 |
| Interpolated compressed sensing for calibrationless parallel MRI reconstruction S Datta, B Deka 2019 National Conference on Communications (NCC), 1-6, 2019 | 6 | 2019 |
| Dictionary Learning-based Multi-Channel ECG Reconstruction using Compressive Sensing B Deka, S Kumar, S Datta IEEE Sensors Journal, 2022 | 5 | 2022 |
| LSTM based Synthesis of 12-lead ECG Signal from a Reduced Lead Set A Kapfo, S Datta, S Dandapat, PK Bora 2022 IEEE International Conference on Signal Processing, Informatics …, 2022 | 5 | 2022 |
| A deep framework for enhancement of diagnostic information in CSMRI reconstruction S Datta, S Dandapat, B Deka Biomedical Signal Processing and Control 71, 103117, 2022 | 5 | 2022 |
| Pattern recognition and machine intelligence B Deka, HU Mullah, S Datta, V Lakshmi, R Ganesan Springer International Publishing, 2019 | 5 | 2019 |
| Block-sparsity based compressed sensing for multichannel ecg reconstruction S Kumar, B Deka, S Datta Pattern Recognition and Machine Intelligence: 8th International Conference …, 2019 | 5 | 2019 |
| Efficient adaptive weighted minimization for compressed sensing magnetic resonance image reconstruction S Datta, B Deka Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and …, 2016 | 5 | 2016 |
| Potential Impact of Data-Centric AI on Society S Kumar, R Sharma, V Singh, S Tiwari, SK Singh, S Datta IEEE Technology and Society Magazine 42 (3), 98-107, 2023 | 3 | 2023 |
Bhabesh DekaDept. of Electronics and Communication Engineering, Tezpur UniversityVerified email at tezu.ernet.in
