Graph attribute embedding via Riemannian submersion learning

Zhao, Haifeng, Robles-Kelly, Antonio, Zhou, Jun, Lu, Jianfeng and Yang, Jing-Yu 2011, Graph attribute embedding via Riemannian submersion learning, Computer vision and image understanding, vol. 115, no. 7, pp. 962-975, doi: 10.1016/j.cviu.2010.12.005.

Attached Files
Name Description MIMEType Size Downloads

Title Graph attribute embedding via Riemannian submersion learning
Author(s) Zhao, Haifeng
Robles-Kelly, AntonioORCID iD for Robles-Kelly, Antonio orcid.org/0000-0002-2465-5971
Zhou, Jun
Lu, Jianfeng
Yang, Jing-Yu
Journal name Computer vision and image understanding
Volume number 115
Issue number 7
Start page 962
End page 975
Total pages 14
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2011-07
ISSN 1077-3142
Keyword(s) Graph embedding
Riemannian geometry
Relational matching
Science & Technology
Technology
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Computer Science
Engineering
Language eng
DOI 10.1016/j.cviu.2010.12.005
Field of Research 0801 Artificial Intelligence And Image Processing
1702 Cognitive Science
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2011, Elsevier Inc.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30119505

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 7 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 9 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Fri, 08 Mar 2019, 10:23:18 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.