{"title":"结合合作分类器投票的两种方法的比较","authors":"J. Franke, E. Mandler","doi":"10.1109/ICPR.1992.201786","DOIUrl":null,"url":null,"abstract":"Two different approaches are described to combine the results of different classifiers. The first approach is based on the Dempster/Shafer theory of evidence and the second one is a statistical approach with some assumptions on the input data. Both approaches were tested for user-dependent recognition of on-line handwritten characters.<<ETX>>","PeriodicalId":34917,"journal":{"name":"模式识别与人工智能","volume":"156 1","pages":"611-614"},"PeriodicalIF":0.0000,"publicationDate":"1992-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"77","resultStr":"{\"title\":\"A comparison of two approaches for combining the votes of cooperating classifiers\",\"authors\":\"J. Franke, E. Mandler\",\"doi\":\"10.1109/ICPR.1992.201786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two different approaches are described to combine the results of different classifiers. The first approach is based on the Dempster/Shafer theory of evidence and the second one is a statistical approach with some assumptions on the input data. Both approaches were tested for user-dependent recognition of on-line handwritten characters.<<ETX>>\",\"PeriodicalId\":34917,\"journal\":{\"name\":\"模式识别与人工智能\",\"volume\":\"156 1\",\"pages\":\"611-614\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"77\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"模式识别与人工智能\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.1992.201786\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"模式识别与人工智能","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/ICPR.1992.201786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
A comparison of two approaches for combining the votes of cooperating classifiers
Two different approaches are described to combine the results of different classifiers. The first approach is based on the Dempster/Shafer theory of evidence and the second one is a statistical approach with some assumptions on the input data. Both approaches were tested for user-dependent recognition of on-line handwritten characters.<>
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
