Empirical study of multi-label classification methods for image annotation and retrieval Nasierding, Gulisong and Kouzani, Abbas Z. 2010, Empirical study of multi-label classification methods for image annotation and retrieval, in DICTA 2010 : Proceedings of the Digital Image Computing : Techniques and Application, DICTA, Sydney, NSW, pp. 617-622. Attached Files Name Description MIMEType Size Downloads kouzani-empiricalstudy-2010.pdf Published version application/pdf 257.03KB 289 Title Empirical study of multi-label classification methods for image annotation and retrieval Author(s) Nasierding, Gulisong Kouzani, Abbas Z. orcid.org/0000-0002-6292-1214 Conference name Digital Image Computing : Techniques and Application Conference (2010 : Sydney, N.S.W.) Conference location Sydney, NSW Conference dates 1-3 Dec. 2010 Title of proceedings DICTA 2010 : Proceedings of the Digital Image Computing : Techniques and Application Editor(s) [Unknown] Publication date 2010 Conference series Australian Pattern Recognition Society Conference Start page 617 End page 622 Total pages 6 Publisher DICTA Place of publication Sydney, NSW Keyword(s) multi-label classification image annotation and retrieval empirical study Summary This paper presents an empirical study of multi-label classification methods, and gives suggestions for multi-label classification that are effective for automatic image annotation applications. The study shows that triple random ensemble multi-label classification algorithm (TREMLC) outperforms among its counterparts, especially on scene image dataset. Multi-label k-nearest neighbor (ML-kNN) and binary relevance (BR) learning algorithms perform well on Corel image dataset. Based on the overall evaluation results, examples are given to show label prediction performance for the algorithms using selected image examples. This provides an indication of the suitability of different multi-label classification methods for automatic image annotation under different problem settings. ISBN 9781424488162 Language eng Field of Research 090609 Signal Processing 080109 Pattern Recognition and Data Mining Socio Economic Objective 890301 Electronic Information Storage and Retrieval Services HERDC Research category E1 Full written paper - refereed HERDC collection year 2010 Copyright notice ©2010, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30032344 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Engineering Open Access Collection Related Links Link Description Connect to conference website 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. 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. Versions Version Filter Type Mon, 24 Jan 2011, 23:38:39 EST Mon, 24 Jan 2011, 23:40:17 EST Fri, 28 Jan 2011, 15:10:55 EST Fri, 28 Jan 2011, 15:11:48 EST Fri, 28 Jan 2011, 15:14:30 EST Fri, 28 Jan 2011, 15:15:12 EST Wed, 02 Feb 2011, 10:43:00 EST Wed, 02 Feb 2011, 14:21:06 EST Thu, 03 Feb 2011, 10:42:30 EST Thu, 03 Feb 2011, 10:43:43 EST Fri, 04 Feb 2011, 13:08:25 EST Fri, 04 Feb 2011, 13:10:13 EST Fri, 04 Feb 2011, 13:17:17 EST Fri, 04 Feb 2011, 13:20:48 EST Fri, 04 Feb 2011, 13:22:19 EST Fri, 04 Feb 2011, 13:25:10 EST Fri, 04 Feb 2011, 13:27:30 EST Mon, 07 Feb 2011, 07:57:01 EST Fri, 16 Mar 2012, 18:33:15 EST Tue, 30 Apr 2013, 11:16:01 EST Thu, 19 Sep 2013, 11:50:11 EST Fri, 06 Feb 2015, 10:41:43 EST Fri, 09 Oct 2015, 17:06:42 EST Mon, 12 Oct 2015, 15:02:34 EST Tue, 06 Sep 2016, 16:20:38 EST Tue, 05 Dec 2017, 10:46:17 EST Fri, 07 Sep 2018, 15:14:37 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 18 times in Scopus Search Google Scholar Access Statistics: 832 Abstract Views, 300 File Downloads  -  Detailed Statistics Created: Mon, 24 Jan 2011, 23:38:38 EST by Abbas Kouzani