Open AccessIdentification of Skin Disease Using Deep Learning
Author(s) -
Shravani Kharat,
Pooja Shinde,
Preeti Malwadkar,
Dipti Chaudhari Prof.
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit2063218
Subject(s) - deep learning , convolutional neural network , identification (biology) , artificial intelligence , computer science , disease , machine learning , acne , artificial neural network , medicine , dermatology , pathology , biology , botany
Globally, skin diseases are among the most common health problems in all humans irrespective of age. Prevention and early detection of these diseases can improve the chance of surviving. This model illustrates the identification of skin diseases providing more objective and reliable solutions using deep learning technology and convolutional neural network approach. In this model, the system design, implementation and identification of common skin diseases such as acne, blister, eczema, warts etc. are explained. The system applies deep learning technology to train itself with various images of skin diseases from the Kaggle platform. The accuracy obtained by using deep learning is 83.23%. The main objective of this system is to achieve maximum accuracy of skin disease prediction. Moreover, if the disease is identified the system provides detailed information about the diseases along with home remedies.