Body joints regression using deep convolutional neural networks Abobakr, Ahmed, Hossny, Mohammed and Nahavandi, Saeid 2017, Body joints regression using deep convolutional neural networks, in SMC 2016 : IEEE International Conference on Systems, Man and Cybernetics, IEEE, Piscataway, N.J., pp. 3281-3287, doi: 10.1109/SMC.2016.7844740. Attached Files Name Description MIMEType Size Downloads hossny-bodyjointsregress-post-2016.pdf Accepted version application/pdf 2.37MB 65 Title Body joints regression using deep convolutional neural networks Author(s) Abobakr, Ahmed orcid.org/0000-0002-6664-2335 Hossny, Mohammed orcid.org/0000-0002-1593-6296 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name Systems, Man and Cybernetics. International Conference (2016 : Budapest, Hungary) Conference location Budapest, Hungary Conference dates 2016/10/09 - 2016/10/12 Title of proceedings SMC 2016 : IEEE International Conference on Systems, Man and Cybernetics Publication date 2017 Start page 3281 End page 3287 Total pages 7 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) Science & Technology Technology Computer Science, Cybernetics Computer Science, Information Systems Computer Science Kinect RGB-D sensors deep learning ConvNet and pose estimation HUMAN POSE ESTIMATION FEATURES ISBN 9781509018970 Language eng DOI 10.1109/SMC.2016.7844740 Indigenous content off Field of Research 080106 Image Processing Socio Economic Objective 920401 Behaviour and Health HERDC Research category E1 Full written paper - refereed Copyright notice ©2016, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30094569 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment Institute for Intelligent Systems Research and Innovation (IISRI) Open Access Collection Related Links Link Description Connect to published version (restricted access) 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 Sun, 30 Apr 2017, 18:22:48 EST Mon, 01 May 2017, 05:00:32 EST Mon, 01 May 2017, 08:09:09 EST Sat, 15 Jul 2017, 02:31:07 EST Fri, 09 Feb 2018, 05:01:45 EST Wed, 07 Mar 2018, 10:45:32 EST Thu, 19 Sep 2019, 06:00:58 EST Mon, 30 Sep 2019, 15:10:30 EST Mon, 30 Sep 2019, 15:36:18 EST Mon, 30 Sep 2019, 15:37:07 EST Mon, 30 Sep 2019, 15:44:08 EST Mon, 30 Sep 2019, 15:53:52 EST Thu, 07 Nov 2019, 11:04:22 EST Filtered Full Citation counts:   Cited 7 times in TR Web of Science Cited 19 times in Scopus Search Google Scholar Access Statistics: 181 Abstract Views, 67 File Downloads  -  Detailed Statistics Created: Sun, 30 Apr 2017, 18:22:48 EST

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