ISIC-2019

ISIC-2019 is a benchmark dataset that contains a collection of dermoscopic images used to evaluate the performance of algorithms in the context of skin lesion classification.

Papers using ISIC-2019 (5)

FederatedFactory: Generative One-Shot Learning for Extremely Non-IID Distributed Scenarios2026FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity2023 · 3 citesFedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation2023 · 3 citesEvidential Federated Learning for Skin Lesion Image Classification2024 · 3 citesFrom Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching2024