Open AccessDesign and Implement of Deep Learning Model to Detect the Melanoma
Author(s) -
Pramod Kumar,
Deepak Sukheja,
G. Ramesh Chandra
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e6611.018520
Subject(s) - melanoma , skin cancer , computer science , deep learning , artificial intelligence , cluster analysis , cancer , process (computing) , set (abstract data type) , task (project management) , stage (stratigraphy) , pattern recognition (psychology) , medicine , cancer research , biology , engineering , paleontology , systems engineering , programming language , operating system
Detecting Skin lesions on the human body is a big task to the doctors in the initial stage because of the low contrast on the body. This skin cancer can be occur due to sun rays. If the disease cannot detect in early stage, there it may cause death to human lives. Here there are some algorithms to predict the melanoma using deep learning techniques. ISIC International Skin Imaging Collaboration Archive set where it provides various images of melanoma and non-melanoma. There are so many challenges to identify the image with melanoma and non-melanoma types of skin cancer. In this paper we applied hair removal algorithm and k-means clustering algorithm where to remove unwanted substances from the original images. To classify the melanoma and non-melanoma skin cancer, this paper proposed prediction process and sequential CNN architecture.