Gabriela E. Martinez, O. Mendoza, J. R. Castro, Antonio Rodríguez Díaz, P. Melin, O. Castillo
{"title":"Comparison between Choquet and Sugeno integrals as aggregation operators for pattern recognition","authors":"Gabriela E. Martinez, O. Mendoza, J. R. Castro, Antonio Rodríguez Díaz, P. Melin, O. Castillo","doi":"10.1109/NAFIPS.2016.7851628","DOIUrl":null,"url":null,"abstract":"In this paper, a comparison of the Choquet and Sugeno integrals is presented. The proposed methods enable the calculation of the Choquet and Sugeno integrals to combine multiple source of information with a degree of uncertainty. The methods are used to combine the modules output of a modular neural network for face recognition and a comparison is performed. In this paper, the focus is on aggregation operators that use measures as inputs, in particular the Choquet and Sugeno integrals. Recognition results with the Choquet integral are better or comparable to results produced by Sugeno integral.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2016.7851628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In this paper, a comparison of the Choquet and Sugeno integrals is presented. The proposed methods enable the calculation of the Choquet and Sugeno integrals to combine multiple source of information with a degree of uncertainty. The methods are used to combine the modules output of a modular neural network for face recognition and a comparison is performed. In this paper, the focus is on aggregation operators that use measures as inputs, in particular the Choquet and Sugeno integrals. Recognition results with the Choquet integral are better or comparable to results produced by Sugeno integral.