Open AccessVision-Based Skin Disease Identification Using Deep Learning
Author(s) -
R. Bhavani,
AUTHOR_ID,
Vallakati Bhanu Prakash,
R.V Kumaresh,
R. Srinivasan,
AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f9391.088619
Subject(s) - convolutional neural network , artificial intelligence , deep learning , computer science , logistic regression , feature extraction , identification (biology) , disease , feature (linguistics) , machine learning , skin lesion , pattern recognition (psychology) , medicine , dermatology , pathology , linguistics , philosophy , botany , biology
Skin disease is the most common health problems worldwide.Human skin is one of the difficult areas topredict. The difficulty is due to rough areas, irregular skin tones, various factors like burns, moles. We have to identify the diseases excluding these factors.In a developing country like India, it is expensive for a large number of people to go to the dermatologist for their skin disease problem.Every year a large number of population in developing countries like India suffer due to different types of skin diseases. So the need for automatic skin disease prediction is increasing for the patients and as well as the dermatologist. In this paper, a method is proposed that uses computer vision-based techniques to detectvariouskinds of dermatological skin diseases. Inception_v3, Mobilenet, Resnetare three deep learning algorithms used for feature extraction in a medical image and machine learning algorithm namely Logistic Regression is used for training and testing the medical images.Using the combined architecture of the three convolutional neural networks considerable efficiency can be achieved.