10 citations · 11 across the 6 of their papers we have counts for
6 papers
Understanding the Mechanisms of Deep Transfer Learning for Medical Images
Hariharan Ravishankar, Prasad Sudhakar, Rahul Venkataramani +4
The ability to automatically learn task specific feature representations has led to a huge success of deep learning methods. When large training data is scarce, such as in medical…
Filter sharing: Efficient learning of parameters for volumetric convolutions
Rahul Venkataramani, Sheshadri Thiruvenkadam, Prasad Sudhakar +2
Typical convolutional neural networks (CNNs) have several millions of parameters and require a large amount of annotated data to train them. In medical applications where training…
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)
L. Jacques, C. De Vleeschouwer, Y. Boursier +64
The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between interna…
Compressive Imaging and Characterization of Sparse Light Deflection Maps
Prasad Sudhakar, Laurent Jacques, Xavier Dubois +2
Light rays incident on a transparent object of uniform refractive index undergo deflections, which uniquely characterize the surface geometry of the object. Associated with each po…
Compressive Schlieren Deflectometry
Prasad Sudhakar, Laurent Jacques, Xavier Dubois +2
Schlieren deflectometry aims at characterizing the deflections undergone by refracted incident light rays at any surface point of a transparent object. For smooth surfaces, each su…
Well-posedness of the permutation problem in sparse filter estimation with lp minimization
Alexis Benichoux, Prasad Sudhakar, Frédéric Bimbot +1
Convolutive source separation is often done in two stages: 1) estimation of the mixing filters and 2) estimation of the sources. Traditional approaches suffer from the ambiguities…