An Introduction to Deep Learing in Image Recognition （3） AutoEncoder and Anomaly Detection

Abstract

Deep learning has realized image classification methods by a data-driven mechanism. It can be said that the relationship between the input data and the correct answer was learned from a large amount of data. When tackling an image classification problem using this principle, it is necessary to collect a large amount of data on rare events in order to deal with rare events, but this can be an impossible task in reality. Anomaly detection is a unique approach that realizes the separation of rare events based on an idea of defining the range of normal features using a large amount of normal data and determining the degree of abnormality by deviation from it. The image feature extraction method using an autoencoder and its evaluation method was described in this course.