{"title":"应用细胞神经网络动态图像表示","authors":"Tang Tang, R. Tetzlaff","doi":"10.1109/ECCTD.2013.6662224","DOIUrl":null,"url":null,"abstract":"In this paper we discuss in detail the feasibility of implementation and realization of uncoupled Cellular Neural Networks (CNN) systems for image representation. Applying CNN systems for representation of binary image patterns with sparse distribution of points as an example for a possible application is studied here. The test results show a high quality of representation with this method and proved it to be a possible way to implement the proposed CNN structures in practical application.","PeriodicalId":342333,"journal":{"name":"2013 European Conference on Circuit Theory and Design (ECCTD)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applying Cellular Neural Networks dynamics for image representation\",\"authors\":\"Tang Tang, R. Tetzlaff\",\"doi\":\"10.1109/ECCTD.2013.6662224\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we discuss in detail the feasibility of implementation and realization of uncoupled Cellular Neural Networks (CNN) systems for image representation. Applying CNN systems for representation of binary image patterns with sparse distribution of points as an example for a possible application is studied here. The test results show a high quality of representation with this method and proved it to be a possible way to implement the proposed CNN structures in practical application.\",\"PeriodicalId\":342333,\"journal\":{\"name\":\"2013 European Conference on Circuit Theory and Design (ECCTD)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 European Conference on Circuit Theory and Design (ECCTD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECCTD.2013.6662224\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 European Conference on Circuit Theory and Design (ECCTD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECCTD.2013.6662224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applying Cellular Neural Networks dynamics for image representation
In this paper we discuss in detail the feasibility of implementation and realization of uncoupled Cellular Neural Networks (CNN) systems for image representation. Applying CNN systems for representation of binary image patterns with sparse distribution of points as an example for a possible application is studied here. The test results show a high quality of representation with this method and proved it to be a possible way to implement the proposed CNN structures in practical application.