Research on SVM and KNN Classifiers for Skin Cancer Detection

  • et al.
N/ACitations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Generally, a not unusual skin ailment in human disorder. In laptop imaginative and prescient applications, coloration is a sturdy indication for this sickness. This machine identifies pores and skin cancer based totally on the picture of the pores and skin. Initially, the skin image is filtered using filters and segmented Gausian the use of energetic contour segmentation. Segmented pix are fed as an input to the feature extraction. Pictures extracted classified the use of class strategies such as Support Vector Machine classifiers(SVM) and k Nearest Neighbor(kNN) classifiers. SVM classifier provided better results than kNN classifier

Cite

CITATION STYLE

APA

Murugan, A., Nair, Dr. S. A. H., & Kumar, Dr. K. P. S. (2019). Research on SVM and KNN Classifiers for Skin Cancer Detection. International Journal of Engineering and Advanced Technology, 9(2), 4627–4632. https://doi.org/10.35940/ijeat.b5117.129219

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free