Seybold Report ISSN: 1533-9211
Deepa Patnaik
Assistant Professor, Department of Electroincs and Communication Engineering, Women’s Engineering College ,Hyderabad ,India, swec.deepa@gmail.com
B. Akhila
U.G Department of Electronics and Communication Engineering, Sridevi Women’s Engineering College, Vattinagulapally, Gandipet, R. R. DIST- 500075, India, akhilabattini@gmail.com
B. Kavya
U.G Department of Electronics and Communication Engineering, Sridevi Women’s Engineering College, Vattinagulapally, Gandipet, R. R. DIST- 500075, India, kavyabattini123@gmail.com
M. Thanusha
U.G Department of Electronics and Communication Engineering, Sridevi Women’s Engineering College, Vattinagulapally, Gandipet, R. R. DIST- 500075, India, thanushareddymallepalli@gmail.com
Vol 17, No 07 ( 2022 ) | DOI: 10.5281/zenodo.6879688 | Licensing: CC 4.0 | Pg no: 259-265 | Published on: 25-07-2022
Abstract
People are concern more about skin diseases rather than any other diseases. Skin diseases are caused mainly due to virus, bacteria and food intake. The most common skin disease occurring in the youth is Acne. Skin diseases are the conditions that affect your skin. These diseases may cause rashes, inflammation’s diseases treatment may include ointments and life style changes. Laser treatments are used to identify and treat the disease but they are expensive.so, Deep learning algorithms is used for detecting the skin disease at early stage. A data set of images has been taken for classifying the skin diseases that may include Actinic keratosis, melanoma, Nevus. Using CNN Algorithms 70% accuracy is achieved and by using Alex Net 80% Accuracy is achieved for classifying the skin disease.
Keywords:
CNN, Alex Net, Deep learning, skin disease