In this paper, a neural network based face recognition system is presented. One of the main problems encountered when using neural networks for face recognition is luck of enough training data. This is because, in most cases, only one image per subject is available. Therefore, one of our objectives is to solve the problem of luck of enough data to train neural networks. For each image we "increase" the data available by several processes for example, mirroring of the image, using color, edges information, etc. The neural network is trained using structural learning to reduce its size. To represent the face color, the YIQ and the XYZ color spaces are used. © Springer-Verlag 2004.
CITATION STYLE
Karungaru, S., Fukumi, M., & Akamatsu, N. (2004). Recognizing frontal faces using neural networks. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3214, 1045–1050. https://doi.org/10.1007/978-3-540-30133-2_139
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