Concept Preserving Hashing for Semantic Image Retrieval with Concept Drift
- Submitting institution
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University of Ulster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 85800937
- Type
- D - Journal article
- DOI
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10.1109/TCYB.2019.2955130
- Title of journal
- IEEE Transactions on Cybernetics
- Article number
- -
- First page
- 1
- Volume
- 0
- Issue
- -
- ISSN
- 2168-2267
- Open access status
- Not compliant
- Month of publication
- December
- Year of publication
- 2019
- URL
-
-
- 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
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2
- Research group(s)
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B - Artificial Intelligence Research Centre
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- <17> This paper presents a solution to incremental image hashing, an important operation for content-based image retrieval from databases. This work was conducted during the first author’s visit to Ulster as a visiting PhD scholar in 2017/18. It has informed a project on Deep and Broad Learning funded by Natural Science Foundation of China (Grant No. 61876066, 01/2019-12/2022), and another project on Multimodal Video Search by Examples funded by EPSRC (EP/V002740/1, £720,502, 10/2020-09/2023). It also consolidates the long-time collaboration between Ulster University and South China University of Technology.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -