To evaluate the effectiveness of the proposed method for anomaly detection and localization, extensive experiments are conducted on three widely-used anomaly detection datasets. The encouraging ...

There are several remaining open questions in the area of flow-based anomaly detection, e.g., how to do meaningful evaluations of anomaly detection mechanisms; how to get conclusive information about ...

To reduce the model training time, transfer learning is used to migrate the trained anomaly detection model between different regions of an ocean area or between similar ocean areas. Moreover, an ...

Recently, vision-language models (e.g. CLIP) have demonstrated remarkable performance in zero-shot anomaly detection (ZSAD ... Specifically, a prompt flow module is designed to learn both ...

Anomaly detection is a machine learning task that ... You can use PyTorch's nn.Module class to define the encoder and decoder layers, and FastAI's Learner class to wrap the model, optimizer ...