Anomaly Detection with Neural Network Using a Generator

Alexander S. Markov, Evgeny Yu. Kotlyarov, Natalia P. Anosova (), Vladimir A. Popov (), Yakov M. Karandashev () and Darya E. Apushkinskaya ()
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Alexander S. Markov: Peoples’ Friendship University of Russia (RUDN University)
Evgeny Yu. Kotlyarov: Peoples’ Friendship University of Russia (RUDN University)
Natalia P. Anosova: Peoples’ Friendship University of Russia (RUDN University)
Vladimir A. Popov: Peoples’ Friendship University of Russia (RUDN University)
Yakov M. Karandashev: Peoples’ Friendship University of Russia (RUDN University)
Darya E. Apushkinskaya: Peoples’ Friendship University of Russia (RUDN University)

A chapter in Data Analysis and Optimization, 2023, pp 215-224 from Springer

Abstract: Abstract This paper concerns with the problem of detecting anomalies on X-ray images taken by Full Body Scanners (FBS). Our previous work describes the sequence of image preprocessing methods used to convert the original images, which are produced with FBS, to an images with visually distinguishable anomalies. In this paper we focus on development of the proposed methods, including the addition of preprocessing methods and the creation of generator which can produce synthetic anomalies. Examples of processed images are given. The results of using a neural network for anomaly detection are shown.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-031-31654-8_14

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DOI: 10.1007/978-3-031-31654-8_14

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