SKIN CANCER DETECTION USING CNN
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SKIN CANCER DETECTION USING CNN
Shanmuga Priya V 1
shanmugapriyav@skasc.ac.in
Department of Computer science (of Affiliation)
Sri Krishna Arts and Science College (of Affiliation)
Coimbatore, India
Ranjanishri M 2
ranjanishrim24@gmail.com
Department of Computer science (of Affiliation)
Sri Krishna Arts and Science College (of Affiliation)
Coimbatore, India
Abstract - Skin cancer is one of the deadliest types of cancer. However: it's likely to spread to other areas of the body, if it isn't diagnosed and treated beforehand on. It's primarily caused by abnormal skin cell development, which occurs frequently when the body is exposed to sun. The Surveillance likewise, relating skin nasty development in its early stages is a precious and delicate process. It's graded according to where it grows and what type of cell it is. The bracket of lesions necessitates a high position of perfection and recall the end is to propose a system that uses a complication Neural Network to diagnose skin cancer and classify it into colourful groups. Image recognition and a deep literacy algorithm are used in the opinion process.
KEYWORDS- Skin Cancer, Convolutional Neural Networks, Early opinion Lesion Bracket, Data Augmentation, HAM- 10000 Dataset, rudimentary Cell Melanoma, Scaled Cell Melanoma, nasty Carcinoma, Actinic Keratosis, Regularization ways, Batch Normalization.