Enhancing baggage inspection through computer vision analysis of x-ray images-Reference-Cited by-同舟云学术

Enhancing baggage inspection through computer vision analysis of x-ray images

Published:2023-12-15 Issue:1 Volume:17 Page:
ISSN:1938-7741
Container-title:Journal of Transportation Security
language:en
Short-container-title:J Transp Secur

Author:

Sarai Wisarut,Monbut Napasakon,Youngchoay Natchapat,Phookriangkrai Nithida,Sattabun Thunpitcha,Siriborvornratanakul Thitirat

Publisher

Springer Science and Business Media LLC

Subject

Law,Management Science and Operations Research,Political Science and International Relations,Safety Research,Sociology and Political Science,Transportation

Link

https://link.springer.com/content/pdf/10.1007/s12198-023-00270-4.pdf

Reference22 articles.

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3. Fang C, Liu J, Han P, Chen M, Liao D (2023) Fsvm: A few-shot threat detection method for x-ray security images. Sensors 23(8). https://doi.org/10.3390/s23084069

4. Gao Q, Hong R, Zhu X, Liu X (2021) An x-ray image enhancement algorithm for dangerous goods in airport security inspection. In: Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS). https://doi.org/10.1109/ACCTCS52002.2021.00017

5. Hassan T, Akcay S, Bennamoun M, Khan S, Werghi N (2023) Unsupervised anomaly instance segmentation for baggage threat recognition. J Ambient Intell Human Comput 14:1607–1618. https://doi.org/10.1007/s12652-021-03383-7

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