Understanding the Mechanisms of Deep Transfer Learning for Medical Images H Ravishankar, P Sudhakar, R Venkataramani, S Thiruvenkadam, ... International Workshop on Large-Scale Annotation of Biomedical Data and …, 2016 | 212 | 2016 |
Learning and Incorporating Shape Models for Semantic Segmentation H Ravishankar, R Venkataramani, S Thiruvenkadam, P Sudhakar, ... International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 192 | 2017 |
On resampling detection and its application to detect image tampering S Prasad, KR Ramakrishnan 2006 IEEE International Conference on Multimedia and Expo, 1325-1328, 2006 | 146 | 2006 |
Deep Learning and Data Labeling for Medical Applications H Ravishankar, P Sudhakar, R Venkataramani, S Thiruvenkadam, ... Cham: Springer, 188-196, 2016 | 49 | 2016 |
Understanding the Mechanisms of Deep Transfer Learning for Medical Images H Ravishankar, P Sudhakar, R Venkataramani, S Thiruvenkadam, ... arXiv preprint arXiv:1704.06040, 2017 | 31 | 2017 |
Double sparsity: Towards blind estimation of multiple channels P Sudhakar, S Arberet, R Gribonval International Conference on Latent Variable Analysis and Signal Separation …, 2010 | 14 | 2010 |
Feature transformers: privacy preserving lifelong learners for medical imaging H Ravishankar, R Venkataramani, S Anamandra, P Sudhakar, P Annangi Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 13 | 2019 |
Compressive imaging and characterization of sparse light deflection maps P Sudhakar, L Jacques, X Dubois, P Antoine, L Joannes SIAM Journal on Imaging Sciences 8 (3), 1824-1856, 2015 | 12 | 2015 |
A sparsity-based method to solve permutation indeterminacy in frequency-domain convolutive blind source separation P Sudhakar, R Gribonval International Conference on Independent Component Analysis and Signal …, 2009 | 11 | 2009 |
Benchmarking Self-Supervised Representation Learning from a million Cardiac Ultrasound images D Anand, P Annangi, P Sudhakar 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 7 | 2022 |
Compressive schlieren deflectometry P Sudhakar, L Jacques, X Dubois, P Antoine, L Joannes 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 5 | 2013 |
Multi-task feature selection neural networks H Ravishankar, BR Sundar, P Sudhakar, R Venkataramani, V Vaidya US Patent 11,232,344, 2022 | 4 | 2022 |
System and method for optimization of deep learning architecture S Thiruvenkadam, SR Ranjan, VP Vaidya, H Ravishankar, ... US Patent 11,017,269, 2021 | 4 | 2021 |
A sparse smoothing approach for Gaussian mixture model based acoustic-to-articulatory inversion P Sudhakar, L Jacques, PK Ghosh 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 4 | 2014 |
System and method for image segmentation using a joint deep learning model H Ravishankar, VP Vaidya, S Thiruvenkadam, R Venkataramani, ... US Patent 10,997,724, 2021 | 3 | 2021 |
Enhancing Z-resolution in CT volumes with deep residual learning U Agrawal, A Hegde, R Langoju, P Sudhakar, BD Patil, RK Sundar, Y Imai, ... Medical Imaging 2021: Image Processing 11596, 612-619, 2021 | 3 | 2021 |
System and method for ultrasound navigation PK Annangi, CK Aladahalli, KS Shriram, P Sudhakar US Patent App. 16/118,466, 2020 | 3 | 2020 |
Sparse smoothing of articulatory features from Gaussian mixture model based acoustic-to-articulatory inversion: benefit to speech recognition. P Sudhakar, PK Ghosh INTERSPEECH, 169-173, 2014 | 3 | 2014 |
Method and system for creating and utilizing a patient-specific organ model from ultrasound image data P Sudhakar, JD Lanning, PK Annangi, M Washburn US Patent 10,952,705, 2021 | 2 | 2021 |
Filter sharing: Efficient learning of parameters for volumetric convolutions R Venkataramani, S Thiruvenkadam, P Sudhakar, H Ravishankar, ... arXiv preprint arXiv:1612.02575, 2016 | 2 | 2016 |