Unsupervised Domain Adaptation for Anomaly Detection Using Autoencoders and Disentangled Latent Representations
Unsupervised anomaly detection based on autoencoder (AE) models has become a widely adopted strategy for condition monitoring in industrial systems, particularly in scenarios where labeled fault data is scarce or unavailable. These approaches typically rely on the assumption that training and testing data follow the sa...