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Melanoma is a major skin cancer type that has a very high death rate. The various sorts of skin lesions cause an inaccurate analysis due to their high resemblance. Precisecategorization of the skin lesions in prematurephasewill allowdermatologists to treat the patients in well timeand save their lives. This is backed by a researchthat shows that 90% of the cases are curable, if identified in the initial phase. With the advancements in the computing power and image classification, automatic detection of the melanoma using computer algorithms has become far reliable. With many methods used, neural networks prove to be the best solution devised to attain the highest accuracy in classifying melanoma through early symptoms. We did our survey to find the drawbacks of recent models that serve this purpose with the goal to overcome them and provide a better solution.