Deep Learning for Detecting Dangerous Objects in X-rays of Luggage

Engineering Proceedings

article

Nikita Andriyanov¹ 

[1] Data Analysis and Machine Learning Department, Financial University under the Government of the Russian Federation

关键词: object detection;    convolutional neural networks;    aviation security;    pattern recognition;    computer vision;   

DOI  :  10.3390/engproc2023033020

来源: mdpi

【 摘 要 】

The investigation presented in this text is the study of object detection algorithms in the task of analyzing images of baggage and hand luggage. A modified version of the YOLOv5 convolutional neural network with additional rechecking based on the VGG-19 network is proposed. The modification is based on transfer learning from the available images. A comparison is made with other known algorithms. The article shows that the application of the proposed model made it possible to achieve the value of the mean average recall (mAR) at the level of 87% for dangerous objects of five classes.

【 授权许可】

Unknown