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

In this paper, a content-based video anomaly detection algorithm (COVAD) is proposed, and its network structure is modified based on the original memory-based video anomaly detection algorithm.

Unlike conventional black-box AI models that flag anomalies without explanation, IFAT produces decision trees that map the ...

Unsupervised anomaly detection algorithms include Autoencoders, K-means, Gaussian Mixture Modelling (GMMs), hypothesis tests-based analysis, and Principal Component Analysis (PCAs).

In the rapidly advancing landscape of Industrial IoT (Internet of Things), cybersecurity has taken on unprecedented importance. The proliferation of connected devices in industrial sectors has ...

Anomaly detection algorithms are leading the charge to take organizations away from the limitations of manually monitoring datasets. In its place is a wave of solutions that can not only make use of ...

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions.

A deep-learning algorithm could detect earthquakes by filtering out city noise The model could uncover quakes that would previously have been dismissed as human-generated vibrations.