{"title":"基于双网格耦合cnn的旋转不变纹理分类","authors":"P. Ungureanu, E. David, L. Goras","doi":"10.1109/NEUREL.2006.341169","DOIUrl":null,"url":null,"abstract":"This paper presents several results of rotation-invariant texture classification using a bank of 2D band-pass CNN filters with approximately circular frequency response. The filters are autonomous two grid coupled CNNs, capable of producing Turing patterns used in the central linear part of their characteristic. The classification performances of the CNN filters are compared with the performances of the ideal circular filters","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"On Rotation Invariant Texture Classification Using Two-Grid Coupled CNNs\",\"authors\":\"P. Ungureanu, E. David, L. Goras\",\"doi\":\"10.1109/NEUREL.2006.341169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents several results of rotation-invariant texture classification using a bank of 2D band-pass CNN filters with approximately circular frequency response. The filters are autonomous two grid coupled CNNs, capable of producing Turing patterns used in the central linear part of their characteristic. The classification performances of the CNN filters are compared with the performances of the ideal circular filters\",\"PeriodicalId\":231606,\"journal\":{\"name\":\"2006 8th Seminar on Neural Network Applications in Electrical Engineering\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 8th Seminar on Neural Network Applications in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2006.341169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2006.341169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On Rotation Invariant Texture Classification Using Two-Grid Coupled CNNs
This paper presents several results of rotation-invariant texture classification using a bank of 2D band-pass CNN filters with approximately circular frequency response. The filters are autonomous two grid coupled CNNs, capable of producing Turing patterns used in the central linear part of their characteristic. The classification performances of the CNN filters are compared with the performances of the ideal circular filters
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