Melanoma Detection on ISIC 2017 (test)
98.52AccuracyChatterjee et al.
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| Chatterjee et al.Features=Regional spatial and spectral features using statistical feature extraction and cross-spectrum analysis, Best classifiers=SVM2026.04 | 98.52 | — | 98.83 | 98.76 | |
| Jaber et al.Features=CNNs features, Best classifiers=Decision trees, SVM, and KNN2026.04 | 98.44 | — | 97.13 | 97.44 | |
| Hosny et al.Features=CNN features, Best classifiers=Residual deep convolutional neural network (RDCNN)2026.04 | 96.29 | — | 97.22 | 94.12 | |
| Okur et al.Features=Pretrained ResNet-101 features, Best classifiers=SVM (RBF)2026.04 | 96.2 | — | 93.6 | 99.8 | |
| Saleh et al.Features=AlexNet, Inception V3, MobileNet V2, ResNet 50, Best classifiers=CNNs2026.04 | 94.5 | — | 96 | 90 | |
| Khan et al.Features=CNN features, Best classifiers=CNN2026.04 | 94.2 | 98 | — | 94.2 | |
| Mahbod et al.Features=Ensembles of deep features from multiple pre-trained and fine-tuned DNNs at multiple layers, Best classifiers=SVM2026.04 | — | 87 | — | — |