{"title":"基于支持向量机的行人识别系统","authors":"A. Ghio, S. Pischiutta","doi":"10.1109/RME.2007.4401836","DOIUrl":null,"url":null,"abstract":"We present here a hardware-friendly structure for the support vector machine (SVM), useful to implement its feedforward phase on resource limited devices, such as field programmable gate arrays (FPGAs), on which a floating-point unit is seldom available. We tested our proposal using an artificial machine-vision benchmark dataset for automotive applications.","PeriodicalId":118230,"journal":{"name":"2007 Ph.D Research in Microelectronics and Electronics Conference","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"A Support Vector Machine based pedestrian recognition system on resource-limited hardware architectures\",\"authors\":\"A. Ghio, S. Pischiutta\",\"doi\":\"10.1109/RME.2007.4401836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present here a hardware-friendly structure for the support vector machine (SVM), useful to implement its feedforward phase on resource limited devices, such as field programmable gate arrays (FPGAs), on which a floating-point unit is seldom available. We tested our proposal using an artificial machine-vision benchmark dataset for automotive applications.\",\"PeriodicalId\":118230,\"journal\":{\"name\":\"2007 Ph.D Research in Microelectronics and Electronics Conference\",\"volume\":\"115 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 Ph.D Research in Microelectronics and Electronics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RME.2007.4401836\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Ph.D Research in Microelectronics and Electronics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RME.2007.4401836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Support Vector Machine based pedestrian recognition system on resource-limited hardware architectures
We present here a hardware-friendly structure for the support vector machine (SVM), useful to implement its feedforward phase on resource limited devices, such as field programmable gate arrays (FPGAs), on which a floating-point unit is seldom available. We tested our proposal using an artificial machine-vision benchmark dataset for automotive applications.