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

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.