自动目标识别系统中目标检测的LIDA-ATR

Muhammad Rizal Khaefi, Dong-Seong Kim
{"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%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automatic detection and decoding of photogrammetric coded targets Human movement detection using home network information and events on smartphones Multi-stage FIR filter design for portable digital spectrum analyzers A pose adaptive eye detection method using 3D face information Learning of social skills for Human-Robot Interaction by hierarchical HMM and interaction dynamics
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1