collaborators

5 papers

cs.CV2026

DMDSC: A Dynamic-Margin Deep Simplex Classifier for Open-Set Recognition on Medical Image Datasets

Vishal, Arnav Aditya, Nitin Kumar +1

Medical imaging datasets are often characterized by extreme class imbalances, where rare pathologies are significantly underrepresented compared to common conditions. This imbalanc…

cs.CV2026

ARMA-C3: A Contrastive ARMA Convolutional Framework for Unsupervised and Semi-supervised Classification

VSS Tejaswi Abburi, Saurabh J. Shigwan, Nitin Kumar

In biomedical and neurodegenerative disorders, accurate and early disease identification remains challenging due to the scarcity of labeled data and the complexity of imaging patte…

cs.CV2026

ARMARecon: An ARMA Convolutional Filter based Graph Neural Network for Neurodegenerative Dementias Classification

VSS Tejaswi Abburi, Ananya Singhal, Saurabh J. Shigwan +1

Early detection of neurodegenerative diseases such as Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD) is essential for reducing the risk of progression to severe disease…

cs.CV2025

UCDSC: Open Set UnCertainty aware Deep Simplex Classifier for Medical Image Datasets

Arnav Aditya, Nitin Kumar, Saurabh Shigwan

Driven by advancements in deep learning, computer-aided diagnoses have made remarkable progress. However, outside controlled laboratory settings, algorithms may encounter several c…

cs.CV2025

Does the Skeleton-Recall Loss Really Work?

Devansh Arora, Nitin Kumar, Sukrit Gupta

Image segmentation is an important and widely performed task in computer vision. Accomplishing effective image segmentation in diverse settings often requires custom model architec…