Hybrid deep feature fusion and ensemble learning for multi-class skin lesion classification

IntroductionAutomated classification of skin lesion remains a challenging task due to high inter-class similarity, intra-class variance and extreme class imbalance in the dermoscopic datasets. To overcome these limitations, the proposed study presents a Hybrid Bi-Feature Network model as HB-Net, in which the convolutional neural networks are fine-tuned to extract features and subsequently machine learning classifier are used for skin lesion classification.MethodsDenseNet201 and ResNet50 are both