{"title":"像素级相似度融合图像分类","authors":"A. P. James","doi":"10.1109/SSD.2010.5585518","DOIUrl":null,"url":null,"abstract":"Recent research shows that local similarity calculations play a significant role in improving the recognition performance of template matching systems. We present a new scheme for parametric similarity calculation and fusion for image classification. State-of-the-art recognition results are obtained using the proposed method for a difficult task involving face images.","PeriodicalId":432382,"journal":{"name":"2010 7th International Multi- Conference on Systems, Signals and Devices","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pixel-level similarity fusion for image classification\",\"authors\":\"A. P. James\",\"doi\":\"10.1109/SSD.2010.5585518\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent research shows that local similarity calculations play a significant role in improving the recognition performance of template matching systems. We present a new scheme for parametric similarity calculation and fusion for image classification. State-of-the-art recognition results are obtained using the proposed method for a difficult task involving face images.\",\"PeriodicalId\":432382,\"journal\":{\"name\":\"2010 7th International Multi- Conference on Systems, Signals and Devices\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 7th International Multi- Conference on Systems, Signals and Devices\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSD.2010.5585518\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 7th International Multi- Conference on Systems, Signals and Devices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSD.2010.5585518","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pixel-level similarity fusion for image classification
Recent research shows that local similarity calculations play a significant role in improving the recognition performance of template matching systems. We present a new scheme for parametric similarity calculation and fusion for image classification. State-of-the-art recognition results are obtained using the proposed method for a difficult task involving face images.
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