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Journal of Applied Sciences
  Year: 2014 | Volume: 14 | Issue: 18 | Page No.: 2149-2155
DOI: 10.3923/jas.2014.2149.2155
 
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Bayesian Face Detection Scheme Based on Support Vector Machine Random Samples

Lu Zhaogan and Sun Jiangfeng

Abstract:
Up to now, the support vector machine theory had been widely used to face detection by reason of its good capability to deal with non-linear high-dimension training problems by small samples. In fact, a large number of facial images were needed to train the support vector machine algorithms, whose complexity were increased by geometric series with training image numbers. So, the hybrid Monte Carlo method and Bayesian support vector machine were combined to find way out for the problems of high-dimension and long training time. The training method of support vector machine was implemented by the hybrid Monte Carlo method. Then, the scheme was verified by experiments that long training time was avoided and good face detection could also be reached.
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How to cite this article:

Lu Zhaogan and Sun Jiangfeng, 2014. Bayesian Face Detection Scheme Based on Support Vector Machine Random Samples. Journal of Applied Sciences, 14: 2149-2155.

DOI: 10.3923/jas.2014.2149.2155

URL: https://scialert.net/abstract/?doi=jas.2014.2149.2155

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