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20152022
most citedMultitask Learning of Temporal Connectionism in Convolutional Networks using a Joint Distribution Loss Function to Simultaneously Identify Tools and Phase in Surgical Videos

13 citations · 33 across the 18 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

eess.IV2019

Significance of Residual Learning and Boundary Weighted Loss in Ischaemic Stroke Lesion Segmentation

Ronnie Rajan, Rachana Sathish, Debdoot Sheet

Radiologists use various imaging modalities to aid in different tasks like diagnosis of disease, lesion visualization, surgical planning and prognostic evaluation. Most of these ta…

eess.IV2019

Adversarially Trained Convolutional Neural Networks for Semantic Segmentation of Ischaemic Stroke Lesion using Multisequence Magnetic Resonance Imaging

Rachana Sathish, Ronnie Rajan, Anusha Vupputuri +2

Ischaemic stroke is a medical condition caused by occlusion of blood supply to the brain tissue thus forming a lesion. A lesion is zoned into a core associated with irreversible ne…

cs.CV20192 cited

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…

cs.LG20191 cited

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…

eess.IV201913 cited

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…

cs.CV20193 cited

Fully Convolutional Neural Network for Semantic Segmentation of Anatomical Structure and Pathologies in Colour Fundus Images Associated with Diabetic Retinopathy

Oindrila Saha, Rachana Sathish, Debdoot Sheet

Diabetic retinopathy (DR) is the most common form of diabetic eye disease. Retinopathy can affect all diabetic patients and becomes particularly dangerous, increasing the risk of b…