{"title":"随机标记过程的一些性质","authors":"Tommy Elfving, Jan-Olof Eklundh","doi":"10.1016/0146-664X(82)90042-9","DOIUrl":null,"url":null,"abstract":"<div><p>In the paper an optimization model for stochastic labeling is formulated and the first-order Kuhn-Tucker conditions of the model are derived. The nonzero fixed points of the relaxation scheme by Rosenfeld, Hummel, and Zucker are then characterized in terms of these conditions. Further a local convergence result is presented and proved and the use of the relaxation scheme for optimization is discussed.</p></div>","PeriodicalId":100313,"journal":{"name":"Computer Graphics and Image Processing","volume":"20 2","pages":"Pages 158-170"},"PeriodicalIF":0.0000,"publicationDate":"1982-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0146-664X(82)90042-9","citationCount":"0","resultStr":"{\"title\":\"Some properties of stochastic labeling procedures\",\"authors\":\"Tommy Elfving, Jan-Olof Eklundh\",\"doi\":\"10.1016/0146-664X(82)90042-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the paper an optimization model for stochastic labeling is formulated and the first-order Kuhn-Tucker conditions of the model are derived. The nonzero fixed points of the relaxation scheme by Rosenfeld, Hummel, and Zucker are then characterized in terms of these conditions. Further a local convergence result is presented and proved and the use of the relaxation scheme for optimization is discussed.</p></div>\",\"PeriodicalId\":100313,\"journal\":{\"name\":\"Computer Graphics and Image Processing\",\"volume\":\"20 2\",\"pages\":\"Pages 158-170\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1982-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0146-664X(82)90042-9\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Graphics and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0146664X82900429\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Graphics and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0146664X82900429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In the paper an optimization model for stochastic labeling is formulated and the first-order Kuhn-Tucker conditions of the model are derived. The nonzero fixed points of the relaxation scheme by Rosenfeld, Hummel, and Zucker are then characterized in terms of these conditions. Further a local convergence result is presented and proved and the use of the relaxation scheme for optimization is discussed.
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