Automated Detection of Threat Materials in X-Ray Baggage Inspection Systems (XBISs)

Manual inspection of baggage X-ray images for the detection of threat materials such as explosives is a tedious and stressful task. We have presented a convolutional neural network (CNN)-based approach for automated detection of threat materials in X-ray images. A deep convolutional generative adver...

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Veröffentlicht in:	IEEE transactions on nuclear science 2022-08, Vol.69 (8), p.1923-1930
Hauptverfasser:	Kayalvizhi, R., S., Malarvizhi, Choudhury, Siddhartha Dhar, Topkar, Anita
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Automation Baggage Classification Convolutional neural network (CNN)-based dual X-ray Baggage (DXB) model deep convolutional generative adversarial network (DCGAN) Detectors dual-energy X-ray baggage images Explosives Explosives detection Generative adversarial networks Generators Image classification Image color analysis Inspection Model accuracy Neural networks organic threat and nonthreat materials Security transfer learning X-ray imaging
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