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Face classification by a random forest

Kouzani, Abbas, Nahavandi, Saeid and Khoshmanesh, K. 2007, Face classification by a random forest, in 2007 IEEE Region 10 Conference : TENCON 2007, IEEE Xplore, Piscataway, N.J., pp. 1-4.

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Title Face classification by a random forest
Author(s) Kouzani, AbbasORCID iD for Kouzani, Abbas orcid.org/0000-0002-6292-1214
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Khoshmanesh, K.
Conference name IEEE Tencon (2007 : Taipei, Taiwan)
Conference location Taipei, Taiwan
Conference dates 30 October to 2 November 2007
Title of proceedings 2007 IEEE Region 10 Conference : TENCON 2007
Editor(s) [Unknown]
Publication date 2007
Conference series IEEE Region 10 Conference
Start page 1
End page 4
Publisher IEEE Xplore
Place of publication Piscataway, N.J.
Summary This paper presents a random forest-based face image classification method. The random forest is an ensemble learning method that grows many classification trees. Each tree gives a classification. The forest selects the classification that has the most votes. Three experiments are performed. The random forest-based method together with several existing approaches are trained and evaluated. The experimental results are presented and discussed.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 1424412722
9781424412723
Language eng
Field of Research 080104 Computer Vision
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2007, IEEE.
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30008082

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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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.