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作者:

Deng, Wanghua (Deng, Wanghua.) | Liang, Xun (Liang, Xun.)

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摘要:

Face detection is a branch field originated from face recognition. In recent years, face detection has shown important significance and value in daily produce and application. A face detection method based on BP neural network and improved AdaBoost algorithm is proposed in this paper. First, Using BP neural network instead of YCbCr gaussian model to build skin color model. Meanwhile, a new method of weight updating for AdaBoost algorithm is proposed. The distance between the threshold and the sample is introduced into the update of weight. Besides the weight has a boundary value. Finally, BP neural network is used to obtain the skin color candidate areas in the image, and the improved AdaBoost algorithm is used to accurately detect the face in the image. Based on our experimental result, the new solution using our BP neural network and improved AdaBoost algorithm performs higher accuracy than the existing approach. © 2018 IEEE.

关键词:

Adaptive boosting Backpropagation Chromium compounds Cloud computing Face recognition Gaussian distribution Image enhancement Neural networks

作者机构:

  • [ 1 ] [Deng, Wanghua]Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Liang, Xun]Beijing University of Technology, Beijing; 100124, China

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来源 :

年份: 2019

页码: 395-399

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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