12 citations · 28 across the 14 of their papers we have counts for
15 papers
On the Role of the Projector in Contrastive Self-Supervised Learning: Last-Layer Rank Dynamics Drive Representation Quality
Siladittya Manna, Priyangshu Mandal, Umapada Pal +1
The dimensional collapse of representations in self-supervised contrastive learning is an ever-present issue. One notable technique to prevent such a collapse of representations is…
Reliability-Aware Weighted Multi-Scale Spatio-Temporal Maps for Heart Rate Monitoring
Arpan Bairagi, Rakesh Dey, Siladittya Manna +1
Remote photoplethysmography (rPPG) allows for the contactless estimation of physiological signals from facial videos by analyzing subtle skin color changes. However, rPPG signals a…
Bridging the Applicator Gap with Data-Doping:Dual-Domain Learning for Precise Bladder Segmentation in CT-Guided Brachytherapy
Suresh Das, Siladittya Manna, Sayantari Ghosh
Performance degradation due to covariate shift remains a major challenge for deep learning models in medical image segmentation. An open question is whether samples from a shifted…
Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation
Siladittya Manna, Suresh Das, Sayantari Ghosh +1
Decentralized federated learning enables learning of data representations from multiple sources without compromising the privacy of the clients. In applications like medical image…
Decorrelation-based Self-Supervised Visual Representation Learning for Writer Identification
Arkadip Maitra, Shree Mitra, Siladittya Manna +2
Self-supervised learning has developed rapidly over the last decade and has been applied in many areas of computer vision. Decorrelation-based self-supervised pretraining has shown…
Correlation Weighted Prototype-based Self-Supervised One-Shot Segmentation of Medical Images
Siladittya Manna, Saumik Bhattacharya, Umapada Pal
Medical image segmentation is one of the domains where sufficient annotated data is not available. This necessitates the application of low-data frameworks like few-shot learning.…
Dynamically Scaled Temperature in Self-Supervised Contrastive Learning
Siladittya Manna, Soumitri Chattopadhyay, Rakesh Dey +2
In contemporary self-supervised contrastive algorithms like SimCLR, MoCo, etc., the task of balancing attraction between two semantically similar samples and repulsion between two…
SelfDocSeg: A Self-Supervised vision-based Approach towards Document Segmentation
Subhajit Maity, Sanket Biswas, Siladittya Manna +4
Document layout analysis is a known problem to the documents research community and has been vastly explored yielding a multitude of solutions ranging from text mining, and recogni…
BYOLMed3D: Self-Supervised Representation Learning of Medical Videos using Gradient Accumulation Assisted 3D BYOL Framework
Siladittya Manna, Rakesh Dey, Souvik Chakraborty
Applications on Medical Image Analysis suffer from acute shortage of large volume of data properly annotated by medical experts. Supervised Learning algorithms require a large volu…
SWIS: Self-Supervised Representation Learning For Writer Independent Offline Signature Verification
Siladittya Manna, Soumitri Chattopadhyay, Saumik Bhattacharya +1
Writer independent offline signature verification is one of the most challenging tasks in pattern recognition as there is often a scarcity of training data. To handle such data sca…
SURDS: Self-Supervised Attention-guided Reconstruction and Dual Triplet Loss for Writer Independent Offline Signature Verification
Soumitri Chattopadhyay, Siladittya Manna, Saumik Bhattacharya +1
Offline Signature Verification (OSV) is a fundamental biometric task across various forensic, commercial and legal applications. The underlying task at hand is to carefully model f…
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…
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…
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…
Self-Supervised Representation Learning for Detection of ACL Tear Injury in Knee MR Videos
Siladittya Manna, Saumik Bhattacharya, Umapada Pal
The success of deep learning based models for computer vision applications requires large scale human annotated data which are often expensive to generate. Self-supervised learning…