Paper Title
Comparative Study on Adaboost Classifier, Generative Adverserial Networks (GAN) and Deep Convolution Neural Network for Image Classification

Abstract
The melanocytic lesions are encountered in comparatively large rates in general population in the growing years. The early diagnosis and treatment of the melanoma demands an effective tool such as dermatoscopy with suitable software for proper detection and classification with high accuracy and efficiency. The most conventionally used algorithm for detecting Melanoma is the ABCDE algorithm. There are wide ranges of classifiers available with their own properties and training process. It is significant to choose a suitable classifier based on the problem to unleash the efficiency of the dermatoscopic images used. Three different types of analogies of totally different base are chosen viz., Adaboost classifier, Genetic Adverserial Networks and finally Deep ConvNet. These three methods are compared based on their results and the best one is predicted. Keywords - Adaboost Classifier, Genetic Adverserial Networks, Melanocytic Lesions, Dermatoscopy