Automatic x-ray image analysis for aviation security within limited computing resources

Author:

Andriyanov N A,Volkov Al K,Volkov An K,Gladkikh A A,Danilov S D

Abstract

Abstract The objective of this work is to develop approaches to automating inspection procedure at airports. The article presents the deficiencies of the existing inspection system, concluding in the negative impact of the human factor. It is proposed to use convolutional neural networks for automatic x-ray image analysis of passenger baggage. The paper presents the results of the convolutional neural network with various input data and architecture within limited computing resources. In a view to further development, this study can contribute to the development of specialized software to help aviation security screeners through partial automation of their work.

Publisher

IOP Publishing

Subject

General Medicine

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Intelligent Computer Vision Systems in the Processing of Baggage and Hand Luggage X-ray Images;Learning and Analytics in Intelligent Systems;2024

2. Deep Learning for Detecting Dangerous Objects in X-rays of Luggage;INTELS’22;2023-06-13

3. ETHSeg: An Amodel Instance Segmentation Network and a Real-world Dataset for X-Ray Waste Inspection;2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2022-06

4. Machine Learning Technologies for Bakery Management Decisions;2022 24th International Conference on Digital Signal Processing and its Applications (DSPA);2022-03-30

5. Detection of objects in the images: from likelihood relationships towards scalable and efficient neural networks;Computer Optics;2022-02

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