A survey on Classification of malignant melanoma and Benign Skin Lesion by Using Machine Learning Techniques

EasyChair Preprint 2611

Abstract

Malignant cancer is one of the many skin most cancers types. Melanoma treatment relies upon the stage of detection. Several techniques which includes clinical and automatic are popular in prognosis of melanoma. Image-based digital diagnosis systems facilitate early cancer detection. The kingdom of the artwork in pc aided analysis device look at recent practices of the above cited systems the use of different processes which includes k-clustering, fuzzy good judgment etc. Research demanding situations related to the different processes concerned in computer aided prognosis of pores and skin cancer are also highlighted. Statistical traits of the dermoscopy picture may be used as efficient discriminating features for detection. Different parameters like texture capabilities, coloration space, form and asymmetry can in addition the expertise of upcoming researchers in the discipline of digital skin prognosis.

Keyphrases: Dermoscopy, Melanoma detection, Skin Cancer Detection, category, laptop aided diagnosis

@booklet{EasyChair:2611,
  author    = {Varun Sharma and Ananth Garg and S. Thenmalar},
  title     = {A survey on Classification of malignant melanoma and Benign Skin Lesion by Using Machine Learning Techniques},
  howpublished = {EasyChair Preprint 2611},
  year      = {EasyChair, 2020}}