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A deep learning framework for the automated inspection of complex dual-energy x-ray cargo imagery

Rogers, TW; Jaccard, N; Griffin, LD; (2017) A deep learning framework for the automated inspection of complex dual-energy x-ray cargo imagery. In: Ashok, A and Franco, ED and Gehm, ME and Neifeld, MA, (eds.) (Proceedings) Conference on Anomaly Detection and Imaging with X-Rays (ADIX) II. SPIE-INT SOC OPTICAL ENGINEERING Green open access

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Type: Proceedings paper
Title: A deep learning framework for the automated inspection of complex dual-energy x-ray cargo imagery
Event: Conference on Anomaly Detection and Imaging with X-Rays (ADIX) II
Location: Anaheim, CA
Dates: 12 April 2017 - 13 April 2017
ISBN-13: 978-1-5106-0876-4
Open access status: An open access version is available from UCL Discovery
DOI: 10.1117/12.2262662
Keywords: Science & Technology, Physical Sciences, Technology, Optics, Imaging Science & Photographic Technology, Cargo screening, Automated Threat Detection, dual-energy X-ray, material discrimination, Deep Learning, Convolutional Neural Networks
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10024869
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