13 citations · 21 across the 6 of their papers we have counts for
8 papers
Adversarially Trained Deep Neural Semantic Hashing Scheme for Subjective Search in Fashion Inventory
Saket Singh, Debdoot Sheet, Mithun Dasgupta
The simple approach of retrieving a closest match of a query image from one in the gallery, compares an image pair using sum of absolute difference in pixel or feature space. The p…
Unit Impulse Response as an Explainer of Redundancy in a Deep Convolutional Neural Network
Rachana Sathish, Debdoot Sheet
Convolutional neural networks (CNN) are generally designed with a heuristic initialization of network architecture and trained for a certain task. This often leads to overparametri…
Multitask Learning of Temporal Connectionism in Convolutional Networks using a Joint Distribution Loss Function to Simultaneously Identify Tools and Phase in Surgical Videos
Shanka Subhra Mondal, Rachana Sathish, Debdoot Sheet
Surgical workflow analysis is of importance for understanding onset and persistence of surgical phases and individual tool usage across surgery and in each phase. It is beneficial…
Simulating Patho-realistic Ultrasound Images using Deep Generative Networks with Adversarial Learning
Francis Tom, Debdoot Sheet
Ultrasound imaging makes use of backscattering of waves during their interaction with scatterers present in biological tissues. Simulation of synthetic ultrasound images is a chall…
Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data
Abhijit Guha Roy, Sailesh Conjeti, Debdoot Sheet +3
Training deep fully convolutional neural networks (F-CNNs) for semantic image segmentation requires access to abundant labeled data. While large datasets of unlabeled image data ar…
DASA: Domain Adaptation in Stacked Autoencoders using Systematic Dropout
Abhijit Guha Roy, Debdoot Sheet
Domain adaptation deals with adapting behaviour of machine learning based systems trained using samples in source domain to their deployment in target domain where the statistics o…