A Machine Learning Framework for Skin Cancer Detection using Transfer Learning
This paper uses deep learning algorithms including InceptionV2, InceptionV3, DenseNet, MobileNet, and VGG19 to improve skin cancer detection. This research aims to improve skin cancer diagnosis. This work aims to determine the most effective evolutionary metrics-based technique to recognizing skin cancer, which is comparable to other diseases. Ultimately, our paper aims to create a realistic skin cancer detection system that uses the best deep learning algorithm. This discovery might improve medical diagnostics, leading to earlier diagnosis and improved healthcare outcomes.
Authors
- M. Augustine
- Mhd Saeed Sharif (ORCID: https://orcid.org/0000-0002-4008-8049)
- Sotirios Spanogianopoulos
Institutions
- University of East London (GB)
- University of Portsmouth (GB)
Publication Details
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1109/ipas63548.2025.10924545
- Citations
- 1
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.05