A fast leading eigenvector approximation for segmentation and grouping Robles-Kelly, Antonio, Sarkar, Sudeep and Hancock, Edwin R 2002, A fast leading eigenvector approximation for segmentation and grouping, in 16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL II, PROCEEDINGS, IEEE COMPUTER SOC,, pp. 639-642. Attached Files Name Description MIMEType Size Downloads Title A fast leading eigenvector approximation for segmentation and grouping Author(s) Robles-Kelly, Antonio orcid.org/0000-0002-2465-5971 Sarkar, Sudeep Hancock, Edwin R Conference name 16th International Conference on Pattern Recognition (ICPR) Conference location QUEBEC CITY, CANADA Conference dates 2002/08/11 - 2002/08/15 Title of proceedings 16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL II, PROCEEDINGS Editor(s) Kasturi, R Laurendeau, D Suen, C Publication date 2002 Series INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION Start page 639 End page 642 Total pages 4 Publisher IEEE COMPUTER SOC Keyword(s) Science & Technology Technology Computer Science, Artificial Intelligence Engineering, Electrical & Electronic Imaging Science & Photographic Technology Computer Science Engineering ISSN 1051-4651 Language eng Indigenous content off HERDC Research category E1.1 Full written paper - refereed Persistent URL http://hdl.handle.net/10536/DRO/DU:30127393 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 19 Jul 2019, 13:40:20 EST Sat, 20 Jul 2019, 05:03:45 EST Sat, 20 Jul 2019, 06:05:05 EST Wed, 02 Dec 2020, 08:55:05 EST Wed, 02 Dec 2020, 08:56:17 EST Wed, 02 Dec 2020, 14:57:24 EST Filtered Full Citation counts:   Cited 2 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 33 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Fri, 19 Jul 2019, 13:40:20 EST

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