Classification of skin cancer images using TensorFlow and inception v3

Author:

Sai V Bhavya,Rao G Narasimha,M Ramya,Sree Y Sujana,T Anuradha

Abstract

It is easy for a human eye to distinguish the images of similar appearance but classifying the images like that of cancer affected skin  requires more expertise. And as the skin cancer cases are increasing globally, it requires more number of human experts. To overcome this problem, many people are working on constructing machine learning classifiers which can detect skin cancer automatically by    classifying skin images. This paper concentrates on developing an approach for predicting skin cancer by classifying images using deep convolution neural network. The proposed work is tested on standard cancer dataset and obtained more than 85% accuracy. 

Publisher

Science Publishing Corporation

Subject

Hardware and Architecture,General Engineering,General Chemical Engineering,Environmental Engineering,Computer Science (miscellaneous),Biotechnology

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DNA Genome Classification with Machine Learning and Image Descriptors;Lecture Notes in Networks and Systems;2023

2. Optimized one-shot neural architecture search for skin cancer classification;Journal of Electronic Imaging;2022-12-22

3. Recognition of human skin diseases using inception-V3 with transfer learning;International Journal of Information Technology;2022-08-10

4. Diagnosis of Lumbar Spondylolisthesis Using Optimized Pretrained CNN Models;Computational Intelligence and Neuroscience;2022-04-13

5. Skin Cancer Detection Using Deep Learning;Futuristic Communication and Network Technologies;2021-10-12

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