{"title":"用多层感知器搜索地雷","authors":"D.J. Shazeer, M. Bello","doi":"10.1109/ICNN.1991.163328","DOIUrl":null,"url":null,"abstract":"The authors describe the use of multilayer perceptrons to solve the problem of distinguishing mine-like objects from clutter. Three increasingly sophisticated and effective approaches were applied against difficult side scan sonar imagery containing a highly cluttered and variable environment. Performances of the three approaches are compared using receiver operating curves (ROCs). Comparisons show that one can achieve a detection rate of 0.97 for a 0.01 false alarm rate. A subset of the networks have been demonstrated on special purpose hardware to run in real time.<<ETX>>","PeriodicalId":296300,"journal":{"name":"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering","volume":"552 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Minehunting with multi-layer perceptrons\",\"authors\":\"D.J. Shazeer, M. Bello\",\"doi\":\"10.1109/ICNN.1991.163328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors describe the use of multilayer perceptrons to solve the problem of distinguishing mine-like objects from clutter. Three increasingly sophisticated and effective approaches were applied against difficult side scan sonar imagery containing a highly cluttered and variable environment. Performances of the three approaches are compared using receiver operating curves (ROCs). Comparisons show that one can achieve a detection rate of 0.97 for a 0.01 false alarm rate. A subset of the networks have been demonstrated on special purpose hardware to run in real time.<<ETX>>\",\"PeriodicalId\":296300,\"journal\":{\"name\":\"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering\",\"volume\":\"552 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNN.1991.163328\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNN.1991.163328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The authors describe the use of multilayer perceptrons to solve the problem of distinguishing mine-like objects from clutter. Three increasingly sophisticated and effective approaches were applied against difficult side scan sonar imagery containing a highly cluttered and variable environment. Performances of the three approaches are compared using receiver operating curves (ROCs). Comparisons show that one can achieve a detection rate of 0.97 for a 0.01 false alarm rate. A subset of the networks have been demonstrated on special purpose hardware to run in real time.<>