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
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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 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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