Grid-based graph attention over masked-autoencoder patch embeddings improves balanced accuracy on ISIC-2018 and ISIC-2019 skin lesion classification over image-level and attention-pooling baselines.
Applied Soft Computing , volume=
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Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis
Grid-based graph attention over masked-autoencoder patch embeddings improves balanced accuracy on ISIC-2018 and ISIC-2019 skin lesion classification over image-level and attention-pooling baselines.