Skin Cancer Detection Using Convolutional Neural Network

Autor:	Mahamudul Hasan, Surajit Das Barman, Ahmed Wasif Reza, Samia Islam
Rok vydání:	2019
Předmět:	integumentary system Computer science business.industry Deep learning Melanoma Feature extraction Image processing Pattern recognition medicine.disease Convolutional neural network Artificial skin medicine Segmentation Artificial intelligence Skin cancer business
Zdroj:	ICCAI
DOI:	10.1145/3330482.3330525
Popis:	Skin cancer is an alarming disease for mankind. The necessity of early diagnosis of the skin cancer have been increased because of the rapid growth rate of Melanoma skin cancer, itś high treatment costs, and death rate. This cancer cells are detected manually and it takes time to cure in most of the cases. This paper proposed an artificial skin cancer detection system using image processing and machine learning method. The features of the affected skin cells are extracted after the segmentation of the dermoscopic images using feature extraction technique. A deep learning based method convolutional neural network classifier is used for the stratification of the extracted features. An accuracy of 89.5% and the training accuracy of 93.7% have been achieved after applying the publicly available data set.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ae175a9801a46493892af5e36f233048 https://doi.org/10.1145/3330482.3330525 Zobrazit plný text záznamu