Research of recognition accuracy of dangerous and safe x-ray baggage images using neural network transfer learning

Autor:	An K. Volkov, A. A. Gladkikh, Al K. Volkov, N. A. Andriyanov
Rok vydání:	2021
Předmět:	Artificial neural network Computer science business.industry Computer vision Artificial intelligence Transfer of learning business
Zdroj:	IOP Conference Series: Materials Science and Engineering. 1061:012002
ISSN:	1757-899X 1757-8981
DOI:	10.1088/1757-899x/1061/1/012002
Popis:	The article considers the use of neural networks to solve the problem of recognizing dangerous and safe objects carried in the luggage of airport passengers. A comparative analysis is performed to define the accuracy achieved on the test sample for different convolutional neural networks. It also explores the influence of various regularizations on the accuracy of a two-class classification. The increased probability of correct recognition is achieved due to augmentation, reset weights and saturation of the network. The method of transfer training is used to increase the efficiency of the recognizer. In this case, a study was carried out for the transfer of various neural networks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c97344b649e27df810e4800afd8deff3 https://doi.org/10.1088/1757-899x/1061/1/012002 Zobrazit plný text záznamu