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

Author:

Andriyanov N A,Volkov Al K,Volkov An K,Gladkikh A A

Abstract

Abstract 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.

Publisher

IOP Publishing

Subject

General Medicine

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