Skin Lesions Classification Using Deep Learning Techniques: Review

Skin cancer is a significant health problem. More than 123,000 new cases per year are recorded. Melanoma the most popular type of skin cancer, leading to more 9000 deaths annually in USA. disease diagnosis getting difficult due visual similarities. While common form other pathology types also fatal. Automatic melanoma screening systems will be useful identifying those cancers appropriately. Advances technology and growth computational capabilities have allowed machine learning deep algorithms analyze lesion images. Deep Convolutional Neural Networks (DCNNs) achieved encouraging results, yet faster for diagnosing fatal diseases need hour. This paper presents survey techniques detection from The aims present review existing state-of-the-art effective models automatically detecting result classifications segmentation images processed better using ensemble algorithm.