Intelligent skin cancer diagnosis using improved particle swarm optimization and deep learning models
- Submitting institution
-
University of Northumbria at Newcastle
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 25208343
- Type
- D - Journal article
- DOI
-
10.1016/j.asoc.2019.105725
- Title of journal
- Applied Soft Computing
- Article number
- 105725
- First page
- -
- Volume
- 84
- Issue
- -
- ISSN
- 1568-4946
- Open access status
- Compliant
- Month of publication
- August
- 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
-
2
- Research group(s)
-
D - Computer Vision and Natural Computing (CVNC)
- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The work features novel evolutionary and deep learning algorithms for medical imaging which led to the invitation of a keynote speech on “Artificial Intelligence (AI)-based Systems for Biomedical Data Analytics and Decision Support”, at International Conference on Biomedical Engineering and Bioinformatics, 25-27/09/2019, Malaysia. It underpins a successful European Regional Development Fund – Industrial Intensive Innovation Programme PhD studentship (10/2019-10/2022), in collaboration with RPPtv. The significance of this research was evidenced by the invitation to be guest editor in special issue on “Deep Learning-based Approaches in Signal Processing and IoT: A pathway to Intelligent Systems (2020-2021)” in Elsevier Pattern Recognition Letters.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
