{"title":"基于注视反馈的模糊层次车模模式识别系统","authors":"Y. Arai, G. Sekiguchi, K. Hirota","doi":"10.1109/KES.1997.616879","DOIUrl":null,"url":null,"abstract":"The \"fuzzy hierarchical pattern recognition using fixation feedback\" method is proposed and it is applied to recognize kinds, i.e., groups of trade names, of cars. In the experiments, image data of fourteen kinds of minicars taken from several directions are used. By comparing the results of the \"non fixation feedback\" method, it has been confirmed that the proposed method could increase efficiency without decreasing accuracy rates of recognition.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fuzzy hierarchical car-model pattern recognition system using fixation feedback\",\"authors\":\"Y. Arai, G. Sekiguchi, K. Hirota\",\"doi\":\"10.1109/KES.1997.616879\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The \\\"fuzzy hierarchical pattern recognition using fixation feedback\\\" method is proposed and it is applied to recognize kinds, i.e., groups of trade names, of cars. In the experiments, image data of fourteen kinds of minicars taken from several directions are used. By comparing the results of the \\\"non fixation feedback\\\" method, it has been confirmed that the proposed method could increase efficiency without decreasing accuracy rates of recognition.\",\"PeriodicalId\":166931,\"journal\":{\"name\":\"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KES.1997.616879\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KES.1997.616879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy hierarchical car-model pattern recognition system using fixation feedback
The "fuzzy hierarchical pattern recognition using fixation feedback" method is proposed and it is applied to recognize kinds, i.e., groups of trade names, of cars. In the experiments, image data of fourteen kinds of minicars taken from several directions are used. By comparing the results of the "non fixation feedback" method, it has been confirmed that the proposed method could increase efficiency without decreasing accuracy rates of recognition.