An approach for adaptive automatic threat recognition within 3D computed tomography images for baggage security screening
Author:
Affiliation:
1. Department of Computer Science, Durham University, UK
2. Information Technology Department, Faculty of Computers and Information, Menoufia University, Egypt
3. Department of Engineering, Durham University, UK
Publisher
IOS Press
Subject
Electrical and Electronic Engineering,Condensed Matter Physics,Radiology Nuclear Medicine and imaging,Instrumentation,Radiation
Reference21 articles.
1. Using deep convolutional neural network architectures for object classification and detection within X-ray baggage security imagery;Akcay;IEEE Transactions on Information Forensics and Security,2018
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3. Random forests;Breiman;Machine Learning,2001
4. Object classification in 3d baggage security computed tomography imagery using visual codebooks;Flitton;Pattern Recognition,2015
5. Detecting bombs in X-ray images of hold baggage: 2D versus 3D imaging;Hättenschwiler;Human Factors,2019
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