Journal article
Face detection from greyscale images using details from categorized wavelet coefficients as features for a dynamic supervised forward propagation network
International Journal of Pattern Recognition and Artificial Intelligence, Vol.23(1), pp.3-15
2009
Abstract
A dynamic counterpropagation network based on the forward only counterpropagation network (CPN) is applied as the classifier for face detection. The network, called the dynamic supervised forward-propagation network (DSFPN) trains using a supervised algorithm that grows dynamically during training allowing subclasses in the training data to be learnt. The network is trained using a reduced dimensionality categorized wavelet coefficients of the image data. Experimental results obtained show that a 94% correct detection rate can be achieved with less than 6% false positives
Details
- Title
- Face detection from greyscale images using details from categorized wavelet coefficients as features for a dynamic supervised forward propagation network
- Authors
- Lee Seng Yeong (Author) - University of NottinghamLi-Minn Ang (Author) - University of NottinghamKing Hann Lim (Author) - University of NottinghamK P Seng (Author) - University of Nottingham
- Publication details
- International Journal of Pattern Recognition and Artificial Intelligence, Vol.23(1), pp.3-15
- Publisher
- World Scientific Publishing Co. Pte Ltd
- Date published
- 2009
- DOI
- 10.1142/S0218001409006977
- ISSN
- 0218-0014; 0218-0014
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab; External
- Language
- English
- Record Identifier
- 99513899502621
- Output Type
- Journal article
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- Web Of Science research areas
- Computer Science, Artificial Intelligence