基于不确定性预测算法的胸部x线图像异常检测

N. Saparkhojayev, Lazzat Zholayeva, Yerzhan Tashkenbayev, D. Tokseit
{"title":"基于不确定性预测算法的胸部x线图像异常检测","authors":"N. Saparkhojayev, Lazzat Zholayeva, Yerzhan Tashkenbayev, D. Tokseit","doi":"10.1109/icecco53203.2021.9663852","DOIUrl":null,"url":null,"abstract":"Histogram of Oriented Gradient (HOG) is one of the popular algorithms for recognizing objects in images with a very high success rate. In image processing techniques hardware reinforcement is one of the key features of studying the large size and complex images to perform. In this study, HOG features were extracted from all locations of a dense grid on an image region and used linear Support Vector Machine (SVM) to classify the combined features.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Abnormality Detection in Chest X-ray Images Using Uncertainty Prediction Algorithms\",\"authors\":\"N. Saparkhojayev, Lazzat Zholayeva, Yerzhan Tashkenbayev, D. Tokseit\",\"doi\":\"10.1109/icecco53203.2021.9663852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Histogram of Oriented Gradient (HOG) is one of the popular algorithms for recognizing objects in images with a very high success rate. In image processing techniques hardware reinforcement is one of the key features of studying the large size and complex images to perform. In this study, HOG features were extracted from all locations of a dense grid on an image region and used linear Support Vector Machine (SVM) to classify the combined features.\",\"PeriodicalId\":331369,\"journal\":{\"name\":\"2021 16th International Conference on Electronics Computer and Computation (ICECCO)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 16th International Conference on Electronics Computer and Computation (ICECCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icecco53203.2021.9663852\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icecco53203.2021.9663852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

定向梯度直方图(Histogram of Oriented Gradient, HOG)是一种常用的图像目标识别算法,具有很高的成功率。在图像处理技术中,硬件增强是研究大尺寸、复杂图像的关键特征之一。在本研究中,从图像区域上密集网格的所有位置提取HOG特征,并使用线性支持向量机(SVM)对组合特征进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abnormality Detection in Chest X-ray Images Using Uncertainty Prediction Algorithms
Histogram of Oriented Gradient (HOG) is one of the popular algorithms for recognizing objects in images with a very high success rate. In image processing techniques hardware reinforcement is one of the key features of studying the large size and complex images to perform. In this study, HOG features were extracted from all locations of a dense grid on an image region and used linear Support Vector Machine (SVM) to classify the combined features.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信