2 citations · 2 across the 2 of their papers we have counts for
3 papers
FLASH: A "Generate Once, Synthesize Many" Framework for Synthetic Anomaly Generation in Industrial Anomaly Detection
Abhay Kumar Das, Rajesh Gangireddy, Ashwin Vaidya +1
Synthetic anomaly generation helps expand industrial anomaly datasets when real defects are scarce or unavailable. Existing approaches lie at two extremes: procedural approaches ar…
Hierarchy-Aware Fine-Tuning of Vision-Language Models
Jiayu Li, Rajesh Gangireddy, Samet Akcay +2
Vision-Language Models (VLMs) learn powerful multimodal representations through large-scale image-text pretraining, but adapting them to hierarchical classification is underexplore…
COOD: Combined out-of-distribution detection using multiple measures for anomaly & novel class detection in large-scale hierarchical classification
L. E. Hogeweg, R. Gangireddy, D. Brunink +3
High-performing out-of-distribution (OOD) detection, both anomaly and novel class, is an important prerequisite for the practical use of classification models. In this paper, we fo…