Anomaly detection is currently an essential quality monitoring process in industrial
production. It is often affected by factors such as under or over reconstruction of images and …

The intelligent detection process for industrial anomalies employs artificial intelligence
methods to classify images that deviate from a normal appearance. Traditional convolutional …

Anomaly detection is an active research field in industrial defect detection and medical
disease detection. However, previous anomaly detection works suffer from unstable training …

Anomaly localization is valuable for improvement of complex production processing in smart
manufacturing system. As the distribution of anomalies is unknowable and labeled data is …

We present a transformer-based image anomaly detection and localization network. Our
proposed model is a combination of a reconstruction-based approach and patch …

For unsupervised anomaly detection and localization, a common approach is learning the
distribution of normal samples and then use it as a criterion to identify abnormalities. This …

The recent rapid development of deep learning has laid a milestone in industrial image
anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning …

In the process of industrial production, anomaly detection is the key link to ensure the high
quality of the product. This paper deeply studies the method of anomaly detection for …

Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid
development. However the recent development of IAD approach has encountered certain …

Detecting anomalies is an essential task in many industries. Current state-of-the-art methods
rely on a large number of parameters for high accuracy, which may not be suitable for …