J. León, Diego Alberto Patiño Cortes, M. AlejandroRestrepo, J. Branch
{"title":"显著信息的计算检测，以识别数字光弹性图像中的高应力和模糊区域","authors":"J. León, Diego Alberto Patiño Cortes, M. AlejandroRestrepo, J. Branch","doi":"10.1364/ISA.2017.IM4E.2","DOIUrl":null,"url":null,"abstract":"Identifying ambiguities and high stress regions in digital photoelasticity is a complex process. We consider such zones as salient information, and process them through saliency algorithms. Hence, highlighted information coincided with ambiguities and stress concentrations.","PeriodicalId":263258,"journal":{"name":"Rundbrief Der Gi-fachgruppe 5.10 Informationssystem-architekturen","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Computational detection of salient information to identify high stress and ambiguity regions in digital photoelasticity images\",\"authors\":\"J. León, Diego Alberto Patiño Cortes, M. AlejandroRestrepo, J. Branch\",\"doi\":\"10.1364/ISA.2017.IM4E.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identifying ambiguities and high stress regions in digital photoelasticity is a complex process. We consider such zones as salient information, and process them through saliency algorithms. Hence, highlighted information coincided with ambiguities and stress concentrations.\",\"PeriodicalId\":263258,\"journal\":{\"name\":\"Rundbrief Der Gi-fachgruppe 5.10 Informationssystem-architekturen\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Rundbrief Der Gi-fachgruppe 5.10 Informationssystem-architekturen\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/ISA.2017.IM4E.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rundbrief Der Gi-fachgruppe 5.10 Informationssystem-architekturen","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/ISA.2017.IM4E.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computational detection of salient information to identify high stress and ambiguity regions in digital photoelasticity images
Identifying ambiguities and high stress regions in digital photoelasticity is a complex process. We consider such zones as salient information, and process them through saliency algorithms. Hence, highlighted information coincided with ambiguities and stress concentrations.
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