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Melanoma classification using EfficientNets and Ensemble of models with different input resolution
, Sagar Karki, Andrew Stranieri
Published in
Pages: 1 - 5
Early and accurate detection of melanoma with data analytics can make treatment more effective. This paper proposes a method to classify melanoma cases using deep learning on dermoscopic images. The method demonstrates that heavy augmentation during training and testing produces promising results and warrants further research. The proposed method has been evaluated on the SIIM-ISIC Melanoma Classification 2020 dataset and the best ensemble model achieved 0.9411 area under the ROC curve on hold out test data.
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JournalACM International Conference Proceeding Series