Manuscript Number : CSEIT194823
Skin Disease Detection Using Machine Learning
Authors(5) :-Prabhakar Satpute, Kuldeepsingh Rajput, Prajakta Jagdale, Satish Chavhan, Prof. Chaitanya Bhosale A skin disease is a particular kind of illness caused by bacteria or an infection. These diseases have various unwanted effects on the skin and keep on increasing over time. It becomes important to recognize these diseases at their initial stage to control it from spreading. These diseases are recognize by using many technologies such as image processing, data mining, artificial neural network (ANN) etc. Now a days ,in area of research related to skin disease detection image processing has played a major role and widely used Techniques like segmentation filtering, image pre-processing, feature extraction and edge detection etc. are part of image processing and are used to recognize the part affected by disease. In this project the database is created on the basis of various images which defines particular skin disease. Data can be stored locally or on cloud. Data will be processed by using A.I. libraries; the methods of regression are used to avoid data storage problems such as big data etc. on the basis of given labeled data the software will train, after providing testing data machine will detect diseases
Prabhakar Satpute Machine Learning, Color Detection, Pixel Detection, Image Conversion ,Data Comparison, Database Management Publication Details Published in : Volume 4 | Issue 8 | September-October 2019 Article Preview
Student, Department of Computer Engineering, Dr. D. Y. Patil School of Engineering, Lohegoan, Savitribai Phule Pune University, Pune, Maharashtra, India
Kuldeepsingh Rajput
Assistant Professor, Department of Computer Engineering, Dr. D. Y. Patil School of Engineering, Lohegoan, Savitribai Phule Pune University, Pune, Maharashtra, India
Prajakta Jagdale
Satish Chavhan
Prof. Chaitanya Bhosale
Date of Publication : 2019-10-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 98-101
Manuscript Number : CSEIT194823
Publisher : Technoscience Academy