Comparison of Convolutional Neural Network Architectures for Robustness Against Common Artefacts in Dermatoscopic Images

INTRODUCTION: Classification of dermatoscopic images via neural networks shows comparable performance to clinicians in experimental conditions but can be affected by artefacts like skin markings or rulers. It is unknown whether specialized neural networks are more robust to artefacts. OBJECTIVES: An...

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Detalles Bibliográficos
Autores principales: Katsch, Florian, Rinner, Christoph, Tschandl, Philipp
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mattioli 1885 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9464520/
https://www.ncbi.nlm.nih.gov/pubmed/36159141
http://dx.doi.org/10.5826/dpc.1203a126

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9464520/
https://www.ncbi.nlm.nih.gov/pubmed/36159141
http://dx.doi.org/10.5826/dpc.1203a126

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