{"title":"基于深度学习的移动设备标牌实时识别信息识别支持系统","authors":"Shigeo Kitamura, Kota Kita, Mitsunori Matsushita","doi":"10.1145/3267782.3274674","DOIUrl":null,"url":null,"abstract":"In this paper, a framework that uses deep learning on a server to recognize signboards in streets with mobile devices is proposed. The proposed framework enables a user to determine the type of shops in his/her location. Our experimental results revealed that the proposed framework recognized signboards with an 86% accuracy within 1 second.","PeriodicalId":126671,"journal":{"name":"Proceedings of the 2018 ACM Symposium on Spatial User Interaction","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-Time Recognition of Signboards with Mobile Device using Deep Learning for Information Identification Support System\",\"authors\":\"Shigeo Kitamura, Kota Kita, Mitsunori Matsushita\",\"doi\":\"10.1145/3267782.3274674\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a framework that uses deep learning on a server to recognize signboards in streets with mobile devices is proposed. The proposed framework enables a user to determine the type of shops in his/her location. Our experimental results revealed that the proposed framework recognized signboards with an 86% accuracy within 1 second.\",\"PeriodicalId\":126671,\"journal\":{\"name\":\"Proceedings of the 2018 ACM Symposium on Spatial User Interaction\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2018 ACM Symposium on Spatial User Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3267782.3274674\",\"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 the 2018 ACM Symposium on Spatial User Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3267782.3274674","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-Time Recognition of Signboards with Mobile Device using Deep Learning for Information Identification Support System
In this paper, a framework that uses deep learning on a server to recognize signboards in streets with mobile devices is proposed. The proposed framework enables a user to determine the type of shops in his/her location. Our experimental results revealed that the proposed framework recognized signboards with an 86% accuracy within 1 second.