Abstract
Abstract: Skin cancer development is one of the conventional deadly disease types, with its cases expanding around the whole world. On the off chance that it's not analyzed in the early stages, it can prompt metastases, bringing about high death rates. Skin disease can be relieved whenever it's identified early. Thus, convenient and exact determination of such malignant growths is a key exploration objective. The early and precise identification of skin cancer has been suggested to be aided by deep-learning algorithms. The paper reviews new research articles based on deep learning methods and feature extraction techniques using LBP for skin cancer classification.
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