Semi‐ and unsupervised learning constitute two pivotal paradigms for extracting structure and meaning from data when explicit labels are sparse or entirely absent. In semi‐supervised learning, a small ...

The proposed industrial anomaly detection model is computationally efficient, memory-friendly, and also suitable for low-light conditions, common in manufacturing environments, making it well-suited ...

Anti-forgetting representation learning method reduces the weight aggregation interference on model memory and augments the ...