3 papers
cs.CV2026
Towards Modality-Agnostic Medical Image Anomaly Detection: A Training-Free Manifold Refinement Approach
Pritam Kar, Gouri Lakshmi S, Saptarshi Bej
Deploying AI-based anomaly detection across diverse clinical imaging settings remains challenging because most existing methods rely on modality-specific architectures, anatomical…
cs.LG2026
Anomaly Detection via Mean Shift Density Enhancement
Pritam Kar, Rahul Bordoloi, Olaf Wolkenhauer +1
Unsupervised anomaly detection stands as an important problem in machine learning. Existing unsupervised anomaly detection algorithms rarely perform well across different anomaly t…
cs.NE2025
Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks
Saptarshi Bej, Muhammed Sahad E, Gouri Lakshmi +3
We introduce Spike Agreement Dependent Plasticity (SADP), a biologically inspired synaptic learning rule for Spiking Neural Networks (SNNs) that relies on the agreement between pre…