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Prasad Sudhakar
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2020 – today
- 2024
- [c17]Hariharan Ravishankar, Prasad Sudhakar, Phaneendra K. Yalavarthy:
TTA-FM: Patient-Specific Test-Time Adaptation Using Foundation Models for Improved Prostate Segmentation in Magnetic Resonance Images. ISBI 2024: 1-5 - 2023
- [c16]Rachana Sathish, Rahul Venkataramani, K. S. Shriram, Prasad Sudhakar:
Task-Driven Prompt Evolution for Foundation Models. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 256-264 - [i6]Rachana Sathish, Rahul Venkataramani, K. S. Shriram, Prasad Sudhakar:
Task-driven Prompt Evolution for Foundation Models. CoRR abs/2310.17128 (2023) - 2022
- [c15]Deepa Anand, Pavan Annangi, Prasad Sudhakar:
Benchmarking Self-Supervised Representation Learning from a million Cardiac Ultrasound images. EMBC 2022: 529-532 - [c14]Pavan Annangi, Prasad Sudhakar, Mike Washburn:
From 2D Ultrasound to Patient-Specific 3D Surface Models for Interventional Guidance. EMBC 2022: 1516-1519 - [c13]Deepa Anand, Rohan Patil, Utkarsh Agrawal, Rahul Venkataramani, Hariharan Ravishankar, Prasad Sudhakar:
Towards Generalization of Medical Imaging AI Models: Sharpness-Aware Minimizers and Beyond. ISBI 2022: 1-5 - [c12]Hariharan Ravishankar, Rohan Patil, Deepa Anand, Vanika Singhal, Utkarsh Agrawal, Rahul Venkataramani, Prasad Sudhakar:
Stochastic Weight Perturbations Along the Hessian: A Plug-and-Play Method to Compute Uncertainty. UNSURE@MICCAI 2022: 80-88 - 2021
- [c11]Utkarsh Agrawal, Aditya Hegde
, Rajesh Langoju, Prasad Sudhakar, Bhushan D. Patil, Sundar R. K., Yasuhiro Imai, Risa Shigemasa, Omi Yasuo, Bipul Das:
Enhancing Z-resolution in CT volumes with deep residual learning. Image Processing 2021
2010 – 2019
- 2019
- [c10]Hariharan Ravishankar, Rahul Venkataramani, Saihareesh Anamandra, Prasad Sudhakar, Pavan Annangi:
Feature Transformers: Privacy Preserving Lifelong Learners for Medical Imaging. MICCAI (4) 2019: 347-355 - 2017
- [c9]Hariharan Ravishankar, Rahul Venkataramani, Sheshadri Thiruvenkadam, Prasad Sudhakar, Vivek Vaidya:
Learning and Incorporating Shape Models for Semantic Segmentation. MICCAI (1) 2017: 203-211 - [i5]Hariharan Ravishankar, Prasad Sudhakar, Rahul Venkataramani, Sheshadri Thiruvenkadam, Pavan Annangi, Narayanan Babu, Vivek Vaidya:
Understanding the Mechanisms of Deep Transfer Learning for Medical Images. CoRR abs/1704.06040 (2017) - 2016
- [c8]Hariharan Ravishankar, Prasad Sudhakar, Rahul Venkataramani, Sheshadri Thiruvenkadam, Pavan Annangi, Narayanan Babu, Vivek Vaidya:
Understanding the Mechanisms of Deep Transfer Learning for Medical Images. LABELS/DLMIA@MICCAI 2016: 188-196 - [i4]Rahul Venkataramani, Sheshadri Thiruvenkadam, Prasad Sudhakar, Hariharan Ravishankar, Vivek Vaidya:
Filter sharing: Efficient learning of parameters for volumetric convolutions. CoRR abs/1612.02575 (2016) - 2015
- [j1]Prasad Sudhakar, Laurent Jacques, Xavier Dubois, Philippe Antoine, Luc Joannes:
Compressive Imaging and Characterization of Sparse Light Deflection Maps. SIAM J. Imaging Sci. 8(3): 1824-1856 (2015) - 2014
- [c7]Prasad Sudhakar, Laurent Jacques
A sparse smoothing approach for Gaussian Mixture Model based Acoustic-to-Articulatory Inversion. ICASSP 2014: 3032-3036 - [c6]Prasad Sudhakar, Prasanta Kumar Ghosh:
Sparse smoothing of articulatory features from Gaussian mixture model based acoustic-to-articulatory inversion: benefit to speech recognition. INTERSPEECH 2014: 169-173 - [i3]Prasad Sudhakar, Laurent Jacques, Xavier Dubois, Philippe Antoine, Luc Joannes:
Compressive Imaging and Characterization of Sparse Light Deflection Maps. CoRR abs/1406.6425 (2014) - [i2]Laurent Jacques, Christophe De Vleeschouwer, Yannick Boursier, Prasad Sudhakar, C. De Mol, Aleksandra Pizurica, Sandrine Anthoine, Pierre Vandergheynst, Pascal Frossard, Cagdas Bilen, Srdan Kitic, Nancy Bertin, Rémi Gribonval, Nicolas Boumal, Bamdev Mishra, Pierre-Antoine Absil, Rodolphe Sepulchre, Shaun Bundervoet, Colas Schretter, Ann Dooms, Peter Schelkens, Olivier Chabiron, François Malgouyres, Jean-Yves Tourneret, Nicolas Dobigeon, Pierre Chainais, Cédric Richard, Bruno Cornelis, Ingrid Daubechies, David B. Dunson, Marie Danková, Pavel Rajmic, Kévin Degraux, Valerio Cambareri, Bert Geelen, Gauthier Lafruit, Gianluca Setti, Jean-François Determe, Jérôme Louveaux, François Horlin, Angélique Drémeau, Patrick Héas, Cédric Herzet, Vincent Duval, Gabriel Peyré, Alhussein Fawzi, Mike E. Davies, Nicolas Gillis, Stephen A. Vavasis, Charles Soussen, Luc Le Magoarou, Jingwei Liang, Jalal Fadili, Antoine Liutkus, David Martina, Sylvain Gigan, Laurent Daudet, Mauro Maggioni, Stanislav Minsker, Nate Strawn, C. Mory, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Ignace Loris, Samuel Vaiter, Mohammad Golbabaee, Dejan Vukobratovic:
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). CoRR abs/1410.0719 (2014) - 2013
- [c5]Prasad Sudhakar, Laurent Jacques
Compressive Schlieren deflectometry. ICASSP 2013: 5999-6003 - 2012
- [c4]Alexis Benichoux, Prasad Sudhakar, Frédéric Bimbot, Rémi Gribonval:
Some Uniqueness Results in Sparse Convolutive Source Separation. LVA/ICA 2012: 196-203 - [i1]Prasad Sudhakar, Laurent Jacques, Xavier Dubois, Philippe Antoine, Luc Joannes:
Compressive Schlieren Deflectometry. CoRR abs/1212.0433 (2012) - 2011
- [c3]Simon Arberet, Prasad Sudhakar, Rémi Gribonval:
A wideband doubly-sparse approach for MITO sparse filter estimation. ICASSP 2011: 2876-2879 - 2010
- [c2]Prasad Sudhakar, Simon Arberet, Rémi Gribonval:
Double Sparsity: Towards Blind Estimation of Multiple Channels. LVA/ICA 2010: 571-578
2000 – 2009
- 2009
- [c1]Prasad Sudhakar, Rémi Gribonval:
A Sparsity-Based Method to Solve Permutation Indeterminacy in Frequency-Domain Convolutive Blind Source Separation. ICA 2009: 338-345
Coauthor Index
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