{"title":"Plenary speaker 1: Continuum fusion: A new theory of inference","authors":"A. Schaum","doi":"10.1109/WHISPERS.2010.5594828","DOIUrl":null,"url":null,"abstract":"By exploiting human insight in the form of a model, methods of composite hypothesis (CH) testing can generate more robust decision algorithms, with a greater ability to generalize, than the alternative “data-driven methods.” The latter include artificial neural networks, genetic algorithms, support vector machines, etc.","PeriodicalId":193944,"journal":{"name":"2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","volume":"85 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WHISPERS.2010.5594828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
By exploiting human insight in the form of a model, methods of composite hypothesis (CH) testing can generate more robust decision algorithms, with a greater ability to generalize, than the alternative “data-driven methods.” The latter include artificial neural networks, genetic algorithms, support vector machines, etc.