Intelligent facial emotion recognition using moth-firefly optimization
- Submitting institution
-
University of Northumbria at Newcastle
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22063493
- Type
- D - Journal article
- DOI
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10.1016/j.knosys.2016.08.018
- Title of journal
- Knowledge-Based Systems
- Article number
- -
- First page
- 248
- Volume
- 111
- Issue
- -
- ISSN
- 0950-7051
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2016
- 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
-
3
- Research group(s)
-
D - Computer Vision and Natural Computing (CVNC)
- Citation count
- 55
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The original evolutionary computation research was recognized by a Best Demo Award in AAMAS2016 (CORE-A*), a keynote speech on “Computational Data Modelling: Methods and Applications”, in International Conference on Mathematical Modelling and Computational Methods in Science and Engineering, 20-22/02/2017, India, a special session on Intelligent Systems for Risk Analysis under Uncertainties in IEEE-sponsored FLINS2018 (CORE-B), and guest editorialship for a special issue on Big Data Centric Computational Intelligence in Bioinformatics and Healthcare in Elsevier Big Data Research (https://www.sciencedirect.com/journal/big-data-research/vol/12/suppl/C). It secured Museum-University Partnership Initiative in collaboration with Society of Antiquaries, Tyne and Wear Archives and Museums, funded by Arts Council England.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -