This repo includes classifier trained to distinct 7 type of skin lesions.
Dataset consists of 10015 images which describe 7 type of lesions. Dataset includes images of following 7 skin lesions:
- Actinic keratoses and intraepithelial carcinoma / Bowen's disease (akiec)
- basal cell carcinoma (bcc)
- benign keratosis-like lesions (solar lentigines / seborrheic keratoses and lichen-planus like keratoses, bkl)
- dermatofibroma (df)
- melanoma (mel)
- melanocytic nevi (nv)
- vascular lesions (angiomas, angiokeratomas, pyogenic granulomas and hemorrhage, vasc)
The following CNN models are used:
- InceptionV3
- Resnet152
- VGG19
- Xception
- Ensemble
| Model | Accuracy |
|---|---|
| InceptionV3 | 0.862 |
| Resnet152 | 0.802 |
| VGG19 | 0.835 |
| Xception | 0.862 |
| Ensemble | 0.875 |
Out of all the algorithms used, Ensemble of Xception, Resnet152, InceptionV3 gives the best accuracy of 0.8753.