Multi-modal curriculum learning for semi-supervised image classification
- Submitting institution
-
Birkbeck College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 177
- Type
- D - Journal article
- DOI
-
10.1109/TIP.2016.2563981
- Title of journal
- IEEE Transactions on Image Processing
- Article number
- -
- First page
- 3249
- Volume
- 25
- Issue
- 7
- ISSN
- 1057-7149
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2016
- URL
-
http://eprints.bbk.ac.uk/id/eprint/15093/
- 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
-
5
- Research group(s)
-
2 - Experimental Data Science
- Citation count
- 125
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first paper to use multi-modal data for image classification. The paper underpinned successful applications for research funding from the Natural Science Foundation of China (61602246, 61973162), Natural Science Foundation of Jiangsu Province (BK20171430) and Fundamental Research Funds for Central Universities (30918011319).
Awarded the Excellent Academic Paper in Natural Science of Nanjing City (3rd prize) and employed in successful applications for funding from the Natural Science Foundation of China (61602246, 61973162), the Natural Science Foundation of Jiangsu Province (BK20171430) and the Fundamental Research Funds for the Central Universities (30918011319). TIP has an h index of 242.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -