Skin disease diagnosis using decision and feature level fusion of deep features
These results demonstrate that while both fusion strategies are effective, DLF slightly outperforms FLF, emphasizing the value of ensemble decision aggregation for robust skin disease classification.
Authors
- Md. Zasim Uddin
- Björn W. Schuller (ORCID: https://orcid.org/0000-0002-6478-8699)
- Md Atiqur Rahman Ahad (ORCID: https://orcid.org/0000-0001-8355-7004)
- Md Shahriar (ORCID: https://orcid.org/0000-0003-4895-2601)
- Md. Nadim Mahamood
Institutions
- University of East London (GB)
- Begum Rokeya University (BD)
- Munich University of Applied Sciences (DE)
- Imperial College London (GB)
- Technical University of Munich (DE)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2025-10-17
- DOI
- https://doi.org/10.3389/fdgth.2025.1478688
- Citations
- 2
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.09