In this study, we explore an image-based method to automate the manual anomaly detection process on quality control plots using deep learning. To do this we trained a Convolutional Neural Network (CNN ...

The increasing accuracy of deep neural networks for solving problems such as speech and image recognition has stoked attention and research devoted to deep learning and AI more generally.

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 ...

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.