새로운 방법론 COFT-AD를 통한 소량 샘플을 활용한 이상 감지
A novel few-shot anomaly detection framework (CAReg) leverages registration as a self-supervised proxy task to achieve category-agnostic representation learning, enabling a single model to detect anomalies in novel categories without requiring fine-tuning.