用机器学习方法识别口腔癌撕裂伤

Prof. Barry Wiling
{"title":"用机器学习方法识别口腔癌撕裂伤","authors":"Prof. Barry Wiling","doi":"10.17762/ijnpme.v7i03.66","DOIUrl":null,"url":null,"abstract":"This Paper describes about Identification of Mouth Cancer laceration Using Machine Learning Approach .The SVM algorithm is used for this purpose. Image segmentation operations are performed using: Resizing an image, Gray scale conversion, Histogram equalization and Classifying the Segmented image using SVM. SVM is used to reduce the complexity faced in the existing system comprising of Texture Segmentation and ANN (Artificial Neural Networks) Algorithm. SVM is a simple Machine Learning algorithm when compared to ANN. The outcome of the paper is to segment and classify the Malignancy from the Non-Malignant region using the classifier SVM. SVM performs the classification based on the dataset that contains the trained images.","PeriodicalId":297822,"journal":{"name":"International Journal of New Practices in Management and Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Identification of Mouth Cancer laceration Using Machine Learning Approach\",\"authors\":\"Prof. Barry Wiling\",\"doi\":\"10.17762/ijnpme.v7i03.66\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This Paper describes about Identification of Mouth Cancer laceration Using Machine Learning Approach .The SVM algorithm is used for this purpose. Image segmentation operations are performed using: Resizing an image, Gray scale conversion, Histogram equalization and Classifying the Segmented image using SVM. SVM is used to reduce the complexity faced in the existing system comprising of Texture Segmentation and ANN (Artificial Neural Networks) Algorithm. SVM is a simple Machine Learning algorithm when compared to ANN. The outcome of the paper is to segment and classify the Malignancy from the Non-Malignant region using the classifier SVM. SVM performs the classification based on the dataset that contains the trained images.\",\"PeriodicalId\":297822,\"journal\":{\"name\":\"International Journal of New Practices in Management and Engineering\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of New Practices in Management and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17762/ijnpme.v7i03.66\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of New Practices in Management and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17762/ijnpme.v7i03.66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

本文介绍了用机器学习方法识别口腔癌撕裂伤的方法,并采用支持向量机算法进行识别。图像分割操作使用:调整图像大小,灰度转换,直方图均衡化和使用SVM对分割图像进行分类。支持向量机用于降低现有纹理分割和人工神经网络算法组成的系统所面临的复杂性。与人工神经网络相比,SVM是一种简单的机器学习算法。本文的结果是使用分类器SVM从非恶性区域中分割和分类恶性区域。SVM基于包含训练图像的数据集执行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Identification of Mouth Cancer laceration Using Machine Learning Approach
This Paper describes about Identification of Mouth Cancer laceration Using Machine Learning Approach .The SVM algorithm is used for this purpose. Image segmentation operations are performed using: Resizing an image, Gray scale conversion, Histogram equalization and Classifying the Segmented image using SVM. SVM is used to reduce the complexity faced in the existing system comprising of Texture Segmentation and ANN (Artificial Neural Networks) Algorithm. SVM is a simple Machine Learning algorithm when compared to ANN. The outcome of the paper is to segment and classify the Malignancy from the Non-Malignant region using the classifier SVM. SVM performs the classification based on the dataset that contains the trained images.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Compressive Strength Properties of Cassava Peel Ash and Wood Ash in Concrete Production Hotel Personnel Retention In Uttar Pradesh: A Study of HYATT Hotels A Study to Reconnoitering the dynamics of Talent Management Procedure at Hotels in Jharkhand Understanding the Concept of Entrepreneurship Management and Its Contribution in Organization A Review of Skin Melanoma Detection Based on Machine Learning
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1