{"title":"基于混合Hopfield网络的三维物体识别方法","authors":"T. D. Brooks, J.H. Kim","doi":"10.1109/SSST.1993.522839","DOIUrl":null,"url":null,"abstract":"A hybrid Hopfield network previously used to solve two-dimensional occluded object recognition problems is adapted to the three-dimensional problem. It is assumed that feature extraction has yielded a set of vertices for the model and a set of vertices for the input object. From these vertices local and relational features are obtained for use in a hybrid Hopfield network graph-matching algorithm used to realize three-dimensional single-input object recognition.","PeriodicalId":260036,"journal":{"name":"1993 (25th) Southeastern Symposium on System Theory","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An approach to three-dimensional object recognition using a hybrid Hopfield network\",\"authors\":\"T. D. Brooks, J.H. Kim\",\"doi\":\"10.1109/SSST.1993.522839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A hybrid Hopfield network previously used to solve two-dimensional occluded object recognition problems is adapted to the three-dimensional problem. It is assumed that feature extraction has yielded a set of vertices for the model and a set of vertices for the input object. From these vertices local and relational features are obtained for use in a hybrid Hopfield network graph-matching algorithm used to realize three-dimensional single-input object recognition.\",\"PeriodicalId\":260036,\"journal\":{\"name\":\"1993 (25th) Southeastern Symposium on System Theory\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1993 (25th) Southeastern Symposium on System Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSST.1993.522839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1993 (25th) Southeastern Symposium on System Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.1993.522839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An approach to three-dimensional object recognition using a hybrid Hopfield network
A hybrid Hopfield network previously used to solve two-dimensional occluded object recognition problems is adapted to the three-dimensional problem. It is assumed that feature extraction has yielded a set of vertices for the model and a set of vertices for the input object. From these vertices local and relational features are obtained for use in a hybrid Hopfield network graph-matching algorithm used to realize three-dimensional single-input object recognition.
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