{"title":"形状识别的熵策略","authors":"D. Geman","doi":"10.1109/WITS.1994.513852","DOIUrl":null,"url":null,"abstract":"We consider a computational strategy for shape recognition based on choosing \"tests\" one at a time in order to remove as much uncertainty as possible about the true hypothesis. The approach is compared with other recognition paradigms in computer vision and illustrated by attempting to classify handwritten digits and track roads from satellite images.","PeriodicalId":423518,"journal":{"name":"Proceedings of 1994 Workshop on Information Theory and Statistics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The entropy strategy for shape recognition\",\"authors\":\"D. Geman\",\"doi\":\"10.1109/WITS.1994.513852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider a computational strategy for shape recognition based on choosing \\\"tests\\\" one at a time in order to remove as much uncertainty as possible about the true hypothesis. The approach is compared with other recognition paradigms in computer vision and illustrated by attempting to classify handwritten digits and track roads from satellite images.\",\"PeriodicalId\":423518,\"journal\":{\"name\":\"Proceedings of 1994 Workshop on Information Theory and Statistics\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1994 Workshop on Information Theory and Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WITS.1994.513852\",\"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 1994 Workshop on Information Theory and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WITS.1994.513852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We consider a computational strategy for shape recognition based on choosing "tests" one at a time in order to remove as much uncertainty as possible about the true hypothesis. The approach is compared with other recognition paradigms in computer vision and illustrated by attempting to classify handwritten digits and track roads from satellite images.
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