50 citations · 92 across the 40 of their papers we have counts for
6 papers · 1 filter
MIO : Mutual Information Optimization using Self-Supervised Binary Contrastive Learning
Siladittya Manna, Umapada Pal, Saumik Bhattacharya
Self-supervised contrastive learning frameworks have progressed rapidly over the last few years. In this paper, we propose a novel loss function for contrastive learning. We model…
Attention W-Net: Improved Skip Connections for better Representations
Shikhar Mohan, Saumik Bhattacharya, Sayantari Ghosh
Segmentation of macro and microvascular structures in fundoscopic retinal images plays a crucial role in the detection of multiple retinal and systemic diseases, yet it is a diffic…
LoOp: Looking for Optimal Hard Negative Embeddings for Deep Metric Learning
Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya +2
Deep metric learning has been effectively used to learn distance metrics for different visual tasks like image retrieval, clustering, etc. In order to aid the training process, exi…
PLSM: A Parallelized Liquid State Machine for Unintentional Action Detection
Dipayan Das, Saumik Bhattacharya, Umapada Pal +1
Reservoir Computing (RC) offers a viable option to deploy AI algorithms on low-end embedded system platforms. Liquid State Machine (LSM) is a bio-inspired RC model that mimics the…
Multipath Graph Convolutional Neural Networks
Rangan Das, Bikram Boote, Saumik Bhattacharya +1
Graph convolution networks have recently garnered a lot of attention for representation learning on non-Euclidean feature spaces. Recent research has focused on stacking multiple l…
SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI Data
Siladittya Manna, Saumik Bhattacharya, Umapada Pal
In medical image analysis, the cost of acquiring high-quality data and their annotation by experts is a barrier in many medical applications. Most of the techniques used are based…