2 papers
cs.CV2026
GATE-AD: Graph Attention Network Encoding For Few-Shot Industrial Visual Anomaly Detection
Aggelos Psiris, Yannis Panagakis, Maria Vakalopoulou +1
Few-Shot Industrial Visual Anomaly Detection (FS-IVAD) comprises a critical task in modern manufacturing settings, where automated product inspection systems need to identify rare…
cs.CV2024
Self-supervised visual learning in the low-data regime: a comparative evaluation
Sotirios Konstantakos, Jorgen Cani, Ioannis Mademlis +4
Self-Supervised Learning (SSL) is a valuable and robust training methodology for contemporary Deep Neural Networks (DNNs), enabling unsupervised pretraining on a 'pretext task' tha…