Anomaly Detection (AD) is a process of identifying/detecting unusual samples which seldom appear or do not even exist in the training dataset. These samples do not confirm the expected behavior and are thus called outliers. Anomalies occur very rarely in the data. AD is strongly correlated to computer vision and image processing tasks such as security, image/video, health, and medical diagnosis, and financial surveillance.

This post summarizes Deep Learning based Image/ Video anomaly Detection survey paper-Image/Video Deep Anomaly Detection: A Survey, discuss the detailed investigation, current challenges, and future research in this direction.

Introduction:

Generally, there are a large number of…

Tamanna Mehta

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