W. T. Sesulihatien, Dia Bitari Mei Yuana, A. Basuki
{"title":"Kinematic Feature for Classifying Larvae: Aedes Larvae and Culex Larvae","authors":"W. T. Sesulihatien, Dia Bitari Mei Yuana, A. Basuki","doi":"10.1109/IES50839.2020.9231938","DOIUrl":null,"url":null,"abstract":"This paper deals with Larvae detection. There are 2 larvae in a similar genre, physically similar, but one larva (Aedes) is a vector of dangerous dengue fever, while Culex is not. Kinematic feature: velocity and acceleration, are employed to distinguish them. Video data of 120 samples are analyzed. The process consists of optical flow for image analysis, velocity and acceleration of motion for drawing the pattern, deviation standard for classifying, and Web-GIS user interface for displaying the result. The accuracy of the system is 91.6%.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"281 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Electronics Symposium (IES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IES50839.2020.9231938","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper deals with Larvae detection. There are 2 larvae in a similar genre, physically similar, but one larva (Aedes) is a vector of dangerous dengue fever, while Culex is not. Kinematic feature: velocity and acceleration, are employed to distinguish them. Video data of 120 samples are analyzed. The process consists of optical flow for image analysis, velocity and acceleration of motion for drawing the pattern, deviation standard for classifying, and Web-GIS user interface for displaying the result. The accuracy of the system is 91.6%.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
