{"title":"第八届MLSP年度大赛:第一名队伍","authors":"Ankit Gupta, Shashwati Mishra, A. Mukerjee","doi":"10.1109/MLSP.2012.6349771","DOIUrl":null,"url":null,"abstract":"Our basic strategy is to examine the spatial neighborhood of the point, P, for its classification. Each point Q in P's neighborhood contributes a binary vote. The sum of these votes, VP, is compared against a threshold τ and access is granted if the value VP is greater than the threshold.","PeriodicalId":262601,"journal":{"name":"2012 IEEE International Workshop on Machine Learning for Signal Processing","volume":"383 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The eighth annual MLSP competition: First place team\",\"authors\":\"Ankit Gupta, Shashwati Mishra, A. Mukerjee\",\"doi\":\"10.1109/MLSP.2012.6349771\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our basic strategy is to examine the spatial neighborhood of the point, P, for its classification. Each point Q in P's neighborhood contributes a binary vote. The sum of these votes, VP, is compared against a threshold τ and access is granted if the value VP is greater than the threshold.\",\"PeriodicalId\":262601,\"journal\":{\"name\":\"2012 IEEE International Workshop on Machine Learning for Signal Processing\",\"volume\":\"383 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Workshop on Machine Learning for Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MLSP.2012.6349771\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Workshop on Machine Learning for Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MLSP.2012.6349771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The eighth annual MLSP competition: First place team
Our basic strategy is to examine the spatial neighborhood of the point, P, for its classification. Each point Q in P's neighborhood contributes a binary vote. The sum of these votes, VP, is compared against a threshold τ and access is granted if the value VP is greater than the threshold.
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