118 citations · 161 across the 15 of their papers we have counts for
15 papers
S2IL: Structurally Stable Incremental Learning
S Balasubramanian, Yedu Krishna P, Talasu Sai Sriram +3
Feature Distillation (FD) strategies are proven to be effective in mitigating Catastrophic Forgetting (CF) seen in Class Incremental Learning (CIL). However, current FD approaches…
ClassifyViStA:WCE Classification with Visual understanding through Segmentation and Attention
S. Balasubramanian, Ammu Abhishek, Yedu Krishna +1
Gastrointestinal (GI) bleeding is a serious medical condition that presents significant diagnostic challenges, particularly in settings with limited access to healthcare resources.…
EXACFS -- A CIL Method to mitigate Catastrophic Forgetting
S Balasubramanian, M Sai Subramaniam, Sai Sriram Talasu +4
Deep neural networks (DNNS) excel at learning from static datasets but struggle with continual learning, where data arrives sequentially. Catastrophic forgetting, the phenomenon of…
Predictive Analysis of Tuberculosis Treatment Outcomes Using Machine Learning: A Karnataka TB Data Study at a Scale
SeshaSai Nath Chinagudaba, Darshan Gera, Krishna Kiran Vamsi Dasu +7
Tuberculosis (TB) remains a global health threat, ranking among the leading causes of mortality worldwide. In this context, machine learning (ML) has emerged as a transformative fo…
Class adaptive threshold and negative class guided noisy annotation robust Facial Expression Recognition
Darshan Gera, Badveeti Naveen Siva Kumar, Bobbili Veerendra Raj Kumar +1
The hindering problem in facial expression recognition (FER) is the presence of inaccurate annotations referred to as noisy annotations in the datasets. These noisy annotations are…
Masked Student Dataset of Expressions
Sridhar Sola, Darshan Gera
Facial expression recognition (FER) algorithms work well in constrained environments with little or no occlusion of the face. However, real-world face occlusion is prevalent, most…