3 papers
cs.CV2026
Listen, Look, and Learn: Learning Without Forgetting through SAM-Audio
Avi Gupta, Nilotpal Sinha, Vishnu Raj +4
Class-Incremental Learning (CIL) aims to continuously learn new classes without forgetting previously acquired knowledge. While recent CIL advances have spurred significant interes…
cs.CV2025
SAMwave: Wavelet-Driven Feature Enrichment for Effective Adaptation of Segment Anything Model
Saurabh Yadav, Avi Gupta, Koteswar Rao Jerripothula
The emergence of large foundation models has propelled significant advances in various domains. The Segment Anything Model (SAM), a leading model for image segmentation, exemplifie…
cs.CV2025
Federated Learning for Commercial Image Sources
Shreyansh Jain, Koteswar Rao Jerripothula
Federated Learning is a collaborative machine learning paradigm that enables multiple clients to learn a global model without exposing their data to each other. Consequently, it pr…