Anomaly detection in images is rapidly emerging as a critical field in both industrial quality control and medical diagnostics. Leveraging deep learning techniques, researchers have developed methods ...

Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing supervised systems while uncovering biological patterns that traditional ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...