Deep Metric Learning for Multi-Label and Multi-Object Image Retrieval
Author:
Affiliation:
1. Department of Information Engineering, Graduate School of Engineering, Hiroshima University
2. Graduate School of Advanced Science and Engineering, Hiroshima University
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E104.D/6/E104.D_2020EDP7226/_pdf
Reference38 articles.
1. [1] T. Kato, T. Kurita, and H. Shimogaki, “Multimedia interaction with image database systems,” ACM SIGCHI Bulletin, vol.22, no.1, pp.52-54, 1990. 10.1145/101288.101299
2. [2] Y. Rui, T.S. Huang, M. Ortega, and S. Mehrotra, “Relevance feedback: a power tool for interactive content-based image retrieval,” IEEE Transactions on Circuits and Systems for Video Technology, vol.8, no.5, pp.644-655, 1998. 10.1109/76.718510
3. [3] T. Takahashi and T. Kurita, “Mixture of subspaces image representation and compact coding for large-scale image retrieval,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, no.7, pp.1469-1479, 2015. 10.1109/tpami.2014.2382092
4. [4] A.K. Alhassan and A.A. Alfaki, “Color and texture fusion-based method for content-based image retrieval,” Proc. 2017 International Conference on Communication, Control, Computing and Electronics Engineering, pp.1-6, IEEE, 2017. 10.1109/iccccee.2017.7867649
5. [5] P.P. Mane and N.G. Bawane, “An effective technique for the content based image retrieval to reduce the semantic gap based on an optimal classifier technique,” Pattern Recognition and Image Analysis, vol.26, no.3, pp.597-607, 2016. 10.1134/s1054661816030159
Cited by 1 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. Research on tree image retrieval method based on twin network multi feature fusion;Energy Reports;2023-06
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