Object Classification in 3D Baggage Security Computed Tomography Imagery using Visual Codebooks
- Submitting institution
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University of Durham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 98961
- Type
- D - Journal article
- DOI
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10.1016/j.patcog.2015.02.006
- Title of journal
- Pattern Recognition
- Article number
- -
- First page
- 2489
- Volume
- 48
- Issue
- 8
- ISSN
- 00313203
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2015
- URL
-
https://doi.org/10.1016/j.patcog.2015.02.006
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
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A - Innovative Computing
- Citation count
- 21
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This 3D CT baggage security imagery research informed inclusion in US government aviation security technology roadmap (see current supporting impact case evidence - “Advanced Algorithm Development for use in X-ray and Computed Tomography Security Scanners used for Transport and Border Security”). Led to invited presentation by Breckon at US Government ADSA workshop in 2016 / 2017 - http://www.northeastern.edu/alert/transitioning-technology/adsa/adsa14/ + http://www.northeastern.edu/alert/transitioning-technology/adsa/adsa17/. Furthermore, Breckon received two grants from both the UK/US government to extend this this work (1: US DHS Contract: HSHQDC-16-A-B008/HSHQDC-16-J-00287 – Sub-contract: 505118-78052 / 2: UK DfT FASS Project: ACC6007893).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -