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Paper Title : Spotting Skin Cancer using CNN

ISSN : 2395-1303
Year of Publication : 2022
10.5281/zenodo.7335336

Authors: P.Harsha,Garipelly Sahruthi, Anampally Vaishnavi, Pokala Varshini

         


Abstract
The development of machine learning has changed many aspects of our life, including how we detect skin malignancies. The most grave kind of skin disease is melanoma, a sort of skin cancer. Medical specialists can treat it, but doing so requires skill and experience. The cancer's stage and the patient's current health condition will determine how the patient is treated. Therefore, SKIN CANCER SPOTTING USING CNN is introduced in order to quickly detect these forms of skin tumours. Modern medical image processing techniques examine images obtained from the skin and images captured under a microscope using a variety of algorithms. The lamination of the excavated structures is done using a Convolutional Neural Network classifier namely based on deep learning. We are experts in convolutional neural networks and have achieved 99.8% prediction accuracy.

Reference
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Keywords
— Data augmentation, Convolutional neural network, Melanoma, malignant, benign, dataset visualization, optimizer, rel-U, Hyperparameter, Convolutional layer