Face Recognition Using DCT and Hierarchical RBF Model

Created by W.Langdon from gp-bibliography.bib Revision:1.7810

@InProceedings{Chen:2006:IDEAL,

• author = "Yuehui Chen and Yaou Zhao",
• title = "Face Recognition Using DCT and Hierarchical RBF Model",
• booktitle = "Intelligent Data Engineering and Automated Learning, IDEAL 2006",
• year = "2009",
• editor = "Emilio Corchado and Hujun Yin and Vicente Botti and Colin Fyfe",
• volume = "4224",
• series = "Lecture Notes in Computer Science",
• pages = "355--362",
• address = "Burgos, Spain",
• month = sep # " 20-23",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, DE, ECGP",
• isbn13 = "978-3-540-45485-4",
• annote = "The Pennsylvania State University CiteSeerX Archives",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.482.9685",
• rights = "Metadata may be used without restrictions as long as the oai identifier remains attached to it.",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.482.9685",
• URL = "http://cilab.ujn.edu.cn/paper/ideal1.pdf",
• DOI = "doi:10.1007/11875581_43",
• abstract = "This paper proposes a new face recognition approach by using the Discrete Cosine Transform (DCT) and Hierarchical Radial Basis Function Network (HRBF) classification model. The DCT is employed to extract the input features to build a face recognition system, and the HRBF is used to identify the faces. Based on the pre-defined instruction/operator sets, a HRBF model can be created and evolved. This framework allows input features selection. The HRBF structure is developed using Extended Compact Genetic Programming (ECGP) and the parameters are optimised by Differential Evolution (DE). Empirical results indicate that the proposed framework is efficient for face recognition.",

}

Genetic Programming entries for Yuehui Chen Yaou Zhao

Citations