{"title":"常用绿色植物识别系统","authors":"Yu Wang, Chang-sheng Li","doi":"10.1109/ICVRV.2018.00035","DOIUrl":null,"url":null,"abstract":"A plant identification system which is designed to integrate local edge algorithms with other classical recognition algorithms in a prototype system is mainly composed of the following two parts. One is the system interface and another is algorithm embedding. A convenient visual environment is provided for users by this system interface, and algorithm functions and other auxiliary functions are integrated. After selecting the system integration algorithms and setting the necessary parameters, the tested plant image is automatically recognized by this system and the corresponding plant images from the database with a brief description are displayed. The tested common green images can be accurately identified and good identification results are obtained by this system.","PeriodicalId":159517,"journal":{"name":"2018 International Conference on Virtual Reality and Visualization (ICVRV)","volume":"338 2-3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Common Green Plants Identification System\",\"authors\":\"Yu Wang, Chang-sheng Li\",\"doi\":\"10.1109/ICVRV.2018.00035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A plant identification system which is designed to integrate local edge algorithms with other classical recognition algorithms in a prototype system is mainly composed of the following two parts. One is the system interface and another is algorithm embedding. A convenient visual environment is provided for users by this system interface, and algorithm functions and other auxiliary functions are integrated. After selecting the system integration algorithms and setting the necessary parameters, the tested plant image is automatically recognized by this system and the corresponding plant images from the database with a brief description are displayed. The tested common green images can be accurately identified and good identification results are obtained by this system.\",\"PeriodicalId\":159517,\"journal\":{\"name\":\"2018 International Conference on Virtual Reality and Visualization (ICVRV)\",\"volume\":\"338 2-3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Virtual Reality and Visualization (ICVRV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRV.2018.00035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Virtual Reality and Visualization (ICVRV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRV.2018.00035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A plant identification system which is designed to integrate local edge algorithms with other classical recognition algorithms in a prototype system is mainly composed of the following two parts. One is the system interface and another is algorithm embedding. A convenient visual environment is provided for users by this system interface, and algorithm functions and other auxiliary functions are integrated. After selecting the system integration algorithms and setting the necessary parameters, the tested plant image is automatically recognized by this system and the corresponding plant images from the database with a brief description are displayed. The tested common green images can be accurately identified and good identification results are obtained by this system.