The proliferation of digital platforms has enabled fraudsters to deploy sophisticated camouflage techniques, such as multi-hop collaborative attacks, to evade detection. Traditional Graph Neural ...

Abstract: Electroencephalogram (EEG) signals are inherently non-stationary and exhibit significant inter-subject variability, leading to pronounced cross-subject distribution shifts that hinder ...

Abstract: Across various domains, Contrastive Learning (CL) has already proven to be a powerful technique but using the Bengali language in the domain of Natural Language Processing (NLP) its' ...

AI-driven image recognition is transforming industries, from healthcare and security to autonomous vehicles and retail. These systems analyze vast amounts of visual data, identifying patterns and ...

This project provides a comprehensive framework for contrastive learning with: ...

Contrastive self-supervised learning has outperformed supervised pretraining on many downstream tasks like segmentation and object detection. However, current methods are still primarily applied to ...