{"title":"基于神经网络的探地雷达目标自动检测与杂波抑制","authors":"H. Youn, Chi-Chih Chen","doi":"10.1117/12.462229","DOIUrl":null,"url":null,"abstract":"Ground penetrating radar (GPR) has been widely used for the detection and location of buried objects. However, the detection method is often subjected to operator's interpretation due to large quantities of data and undesired clutter and noise. Such a detection method is neither reliable nor efficient.","PeriodicalId":256772,"journal":{"name":"International Conference on Ground Penetrating Radar","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Automatic GPR target detection and clutter reduction using neural network\",\"authors\":\"H. Youn, Chi-Chih Chen\",\"doi\":\"10.1117/12.462229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ground penetrating radar (GPR) has been widely used for the detection and location of buried objects. However, the detection method is often subjected to operator's interpretation due to large quantities of data and undesired clutter and noise. Such a detection method is neither reliable nor efficient.\",\"PeriodicalId\":256772,\"journal\":{\"name\":\"International Conference on Ground Penetrating Radar\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Ground Penetrating Radar\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.462229\",\"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 Conference on Ground Penetrating Radar","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.462229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic GPR target detection and clutter reduction using neural network
Ground penetrating radar (GPR) has been widely used for the detection and location of buried objects. However, the detection method is often subjected to operator's interpretation due to large quantities of data and undesired clutter and noise. Such a detection method is neither reliable nor efficient.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
