{"title":"自动目标识别系统中目标检测的LIDA-ATR","authors":"Muhammad Rizal Khaefi, Dong-Seong Kim","doi":"10.1109/ELINFOCOM.2014.6914414","DOIUrl":null,"url":null,"abstract":"This paper proposes scheme called LIDA-ATR (Learning Intelligent Distribution Agent-Automatic Target Recognition). The main idea of this scheme is LIDA integration with object detection feature for the development of automatic target recognition (ATR) system. By using human inspired cognitive systems of LIDA, LIDA-ATR offers autonomous and intelligent solutions that differ with another ATR approaches. Simulation result performed by using sample data represents equilateral and non-equilateral two dimensional objects. Simulation result shows that the proposed scheme has 91.67 % success ratio to detect sample data that placed less than 45 cm from the sensor.","PeriodicalId":360207,"journal":{"name":"2014 International Conference on Electronics, Information and Communications (ICEIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"LIDA-ATR for object detection in Automatic Target Recognition system\",\"authors\":\"Muhammad Rizal Khaefi, Dong-Seong Kim\",\"doi\":\"10.1109/ELINFOCOM.2014.6914414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes scheme called LIDA-ATR (Learning Intelligent Distribution Agent-Automatic Target Recognition). The main idea of this scheme is LIDA integration with object detection feature for the development of automatic target recognition (ATR) system. By using human inspired cognitive systems of LIDA, LIDA-ATR offers autonomous and intelligent solutions that differ with another ATR approaches. Simulation result performed by using sample data represents equilateral and non-equilateral two dimensional objects. Simulation result shows that the proposed scheme has 91.67 % success ratio to detect sample data that placed less than 45 cm from the sensor.\",\"PeriodicalId\":360207,\"journal\":{\"name\":\"2014 International Conference on Electronics, Information and Communications (ICEIC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Electronics, Information and Communications (ICEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELINFOCOM.2014.6914414\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Electronics, Information and Communications (ICEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELINFOCOM.2014.6914414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文提出了LIDA-ATR (Learning Intelligent Distribution Agent-Automatic Target Recognition)方案。该方案的主要思想是将LIDA与目标检测特征相结合,开发自动目标识别(ATR)系统。通过使用LIDA的人类认知系统,LIDA-ATR提供了与其他ATR方法不同的自主和智能解决方案。使用样本数据进行的仿真结果表示等边和非等边二维物体。仿真结果表明,该方法对距离传感器小于45 cm的样本数据的检测成功率为91.67%。
LIDA-ATR for object detection in Automatic Target Recognition system
This paper proposes scheme called LIDA-ATR (Learning Intelligent Distribution Agent-Automatic Target Recognition). The main idea of this scheme is LIDA integration with object detection feature for the development of automatic target recognition (ATR) system. By using human inspired cognitive systems of LIDA, LIDA-ATR offers autonomous and intelligent solutions that differ with another ATR approaches. Simulation result performed by using sample data represents equilateral and non-equilateral two dimensional objects. Simulation result shows that the proposed scheme has 91.67 % success ratio to detect sample data that placed less than 45 cm from the sensor.