Using a Small Dataset in Learning for Object Anomaly Detection
This paper introduces a novel approach to object anomaly detection using an ordered ensemble method with Procrustes distance, emphasizing data efficiency with small training sets. Unlike traditional deep autoencoder methods, which rely on pixel-wise reconstruction and require large datasets (e.g., 200 images per category in the MVTec AD dataset), our method leverages Procrustes distance to […]
