Fig. 1. Structure of residual block

Fig. 2. Flow chart of dermoscopy image classification method

Fig. 3. Examples of seven skin diseases

Fig. 4. Data set classification

Fig. 5. Example of augmented image. (a) Original image; (b) augmented image

Fig. 6. Dividing process of data set

Fig. 7. Examples of secondary data augmentation images. (a) Original image in basic train set; (b) images after secondary data augmentation

Fig. 8. Distribution of training set samples after secondary data augmentation

Fig. 9. Structure of FL-ResNet50 model

Fig. 10. Structure of two kinds of residuals blocks. (a) Identity block; (b) Conv block

Fig. 11. Confusion matrix of classification results

Fig. 12. Loss during training process

Fig. 13. Accuracy during training process