{"title":"基于模糊理论的支持向量机图像情感识别研究","authors":"Junjie Chen, Dawei Zhang, Haifang Li","doi":"10.1109/FBIE.2008.69","DOIUrl":null,"url":null,"abstract":"This paper introduces FSVM, which introjects fuzzy theory to SVM, achieves a classification system which classifies image layer by layer to affective semantic level by FSVM, and proposes one kind of image affective semantics classification method. The difficulty is to establish a mapping from image features to image affective semantics and how to select fitting membership function to test image semantic class. The experimental result shows that the system is simple, fast, effective, and so on, therefore our system is proved to be successful in promoting the image semantic classification to affective semantic level.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Research of SVM Introjecting Fuzzy Theory in Image Affective Recognition\",\"authors\":\"Junjie Chen, Dawei Zhang, Haifang Li\",\"doi\":\"10.1109/FBIE.2008.69\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces FSVM, which introjects fuzzy theory to SVM, achieves a classification system which classifies image layer by layer to affective semantic level by FSVM, and proposes one kind of image affective semantics classification method. The difficulty is to establish a mapping from image features to image affective semantics and how to select fitting membership function to test image semantic class. The experimental result shows that the system is simple, fast, effective, and so on, therefore our system is proved to be successful in promoting the image semantic classification to affective semantic level.\",\"PeriodicalId\":415908,\"journal\":{\"name\":\"2008 International Seminar on Future BioMedical Information Engineering\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Seminar on Future BioMedical Information Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FBIE.2008.69\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Seminar on Future BioMedical Information Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FBIE.2008.69","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Research of SVM Introjecting Fuzzy Theory in Image Affective Recognition
This paper introduces FSVM, which introjects fuzzy theory to SVM, achieves a classification system which classifies image layer by layer to affective semantic level by FSVM, and proposes one kind of image affective semantics classification method. The difficulty is to establish a mapping from image features to image affective semantics and how to select fitting membership function to test image semantic class. The experimental result shows that the system is simple, fast, effective, and so on, therefore our system is proved to be successful in promoting the image semantic classification to affective semantic level.