IOP Conference Series Materials Science and Engineering · 2020 · 12 citations · 3 references
ComputingComputer EngineeringComputer ScienceAutomationComputer VisionMachine LearningAviation SecurityDeep LearningImage AnalysisInspectionPattern RecognitionX-ray DetectionAutomated Image AnalysisAutomated Inspection SystemsAutomated Visual InspectionComputer Vision For InspectionComputer Vision InspectionConvolutional Neural NetworksConvolutional Neural Networks For InspectionInspection Automation
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.
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