Comparison of convolutional neural network architectures for robustness against common artefacts in dermatoscopic images
Introduction: Automated 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 equally affected, or more rob...
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| Format: | Book |
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Mattioli1885,
2022-07-01T00:00:00Z.
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A1234.567 |
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