AdaBoost-CNN: an adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning
- Submitting institution
-
Loughborough University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1985
- Type
- D - Journal article
- DOI
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10.1016/j.neucom.2020.03.064
- Title of journal
- Neurocomputing
- Article number
- -
- First page
- 351
- Volume
- 404
- Issue
- -
- ISSN
- 0925-2312
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2020
- 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
-
2
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The research has attracted interest from commercial organisations including Toyota (TMUK), and Brother-UK Ltd who are requiring sophisticated Video Analytics and Artificial Intelligence algorithms for unbiased recruitment processes. The paper resulted in a collaboration with the Academic Department of Military Rehabilitation who invested in a PhD studentship under the supervision of Dr Cosma, to develop Artificial Intelligence-based models to: classify multi-modal data collected from injured military personnel; and to propose personalised medical interventions.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -