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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Mattioli 1885
2022
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| Materias: | |
| 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 |