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arXiv Computer Vision By Wagner Moreno Schmitz, Marco Antonio de Castro Barbosa, Thiago Magalh\~aes Amaral, Dalcimar Casanova, Jefferson Tales Oliva

A Comparative Evaluation of Pre-trained Convolutional Neural Networks for Melanoma Detection

Read the original on arXiv Computer Vision →

The study compares five pre‑trained convolutional neural networks—ResNet50, VGG16, VGG19, MobileNet, and InceptionV3—for melanoma detection using dermatoscopic and histopathological image datasets. Accuracy varied across models and modalities, with ResNet50 achieving the highest scores (84% on HAM10000 and 83% on CR‑AI4SkIN) and InceptionV3 the lowest (71% on ISIC 2018). The results show that a model’s performance on dermatoscopic images does not necessarily predict its performance on histopathological images.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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