{"title":"ATR算法对场景畸变的敏感性分析:自动目标识别系统性能评估的关键","authors":"M. A. Mohd","doi":"10.1109/SECON.1994.324266","DOIUrl":null,"url":null,"abstract":"This paper presents a methodology to characterize the automatic target recognition (ATR) algorithm performance when it is subjected to geometrical scene distortions. The methodology presented is a parametric variation technique whereby perturbations in sensor parameters are made and the target probability of detection and location determined. The generic methodology developed here can serve as a very useful tool in the test and evaluation of ATR systems used in industrial, scientific, commercial, medical, civil defence, and national defence applications.<<ETX>>","PeriodicalId":119615,"journal":{"name":"Proceedings of SOUTHEASTCON '94","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Sensitivity analysis of ATR algorithms to scene distortions: the key to performance evaluation of automatic target recognition systems\",\"authors\":\"M. A. Mohd\",\"doi\":\"10.1109/SECON.1994.324266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a methodology to characterize the automatic target recognition (ATR) algorithm performance when it is subjected to geometrical scene distortions. The methodology presented is a parametric variation technique whereby perturbations in sensor parameters are made and the target probability of detection and location determined. The generic methodology developed here can serve as a very useful tool in the test and evaluation of ATR systems used in industrial, scientific, commercial, medical, civil defence, and national defence applications.<<ETX>>\",\"PeriodicalId\":119615,\"journal\":{\"name\":\"Proceedings of SOUTHEASTCON '94\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of SOUTHEASTCON '94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.1994.324266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of SOUTHEASTCON '94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.1994.324266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sensitivity analysis of ATR algorithms to scene distortions: the key to performance evaluation of automatic target recognition systems
This paper presents a methodology to characterize the automatic target recognition (ATR) algorithm performance when it is subjected to geometrical scene distortions. The methodology presented is a parametric variation technique whereby perturbations in sensor parameters are made and the target probability of detection and location determined. The generic methodology developed here can serve as a very useful tool in the test and evaluation of ATR systems used in industrial, scientific, commercial, medical, civil defence, and national defence applications.<>
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