Classification of Improvised Explosive Devices Using Multilevel Projective Dictionary Learning With Low-Rank Prior-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Classification of Improvised Explosive Devices Using Multilevel Projective Dictionary Learning With Low-Rank Prior

Published:2022 Issue: Volume:60 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Tivive Fok Hing Chi¹^ORCID,Bouzerdoum Abdesselam²^ORCID,Abeynayake Canicious³^ORCID

Affiliation:

1. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, Australia

2. Information and Computing Technology Division, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

3. Weapons and Combat Systems Division, Defence Science and Technology Group, Edinburgh, SA, Australia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09713872.pdf?arnumber=9713872

Reference68 articles.

1. GPR signal classification with low-rank and convolutional sparse coding representation

2. Leveraging robust principal component analysis to detect buried explosive threats in handheld ground-penetrating radar data;kalika;Proc SPIE,2015

3. Feature Extraction and Classification of Buried Landmine Signals

4. Combination of physics-based and image-based features for landmine identification in ground penetrating radar data

5. Detection and classification of landmines using AR modeling of GPR data

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Detection of explosives in dustbins using deep transfer learning based multiclass classifiers;Applied Intelligence;2024-01

2. Special Issue on Ground Penetrating Radar: Theory, Methods, and Applications;Applied Sciences;2023-08-31

3. A Comprehensive Review of Conventional and Deep Learning Approaches for Ground-Penetrating Radar Detection of Raw Data;Applied Sciences;2023-07-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3