{"title":"自动目标识别的最新发展趋势分析","authors":"Xavier Williams, N. Mahapatra","doi":"10.1109/CSCI49370.2019.00083","DOIUrl":null,"url":null,"abstract":"Automatic object identification (auto-ID) involves techniques for automatically identifying objects using visual features or tags with unique identification codes. These auto-ID systems then transfer the collected identification information to computer systems for further data management. In this paper, we analyze the existing auto-ID techniques for physically tagged objects.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Recent Trends in Automatic Object Identification\",\"authors\":\"Xavier Williams, N. Mahapatra\",\"doi\":\"10.1109/CSCI49370.2019.00083\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic object identification (auto-ID) involves techniques for automatically identifying objects using visual features or tags with unique identification codes. These auto-ID systems then transfer the collected identification information to computer systems for further data management. In this paper, we analyze the existing auto-ID techniques for physically tagged objects.\",\"PeriodicalId\":103662,\"journal\":{\"name\":\"2019 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"volume\":\"156 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCI49370.2019.00083\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI49370.2019.00083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Recent Trends in Automatic Object Identification
Automatic object identification (auto-ID) involves techniques for automatically identifying objects using visual features or tags with unique identification codes. These auto-ID systems then transfer the collected identification information to computer systems for further data management. In this paper, we analyze the existing auto-ID techniques for physically tagged objects.