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Cluster Computing

Erschienen in:

29.12.2017

Hand gesture recognition based on convolution neural network

verfasst von: Gongfa Li, Heng Tang, Ying Sun, Jianyi Kong, Guozhang Jiang, Du Jiang, Bo Tao, Shuang Xu, Honghai Liu

Erschienen in: Cluster Computing | Sonderheft 2/2019

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Abstract

Due to the complexity issue of the hand gesture recognition feature extraction, for example the variation of the light and background. In this paper, the convolution neural network is applied to the recognition of gestures, and the characteristics of convolution neural network are used to avoid the feature extraction process, reduce the number of parameters needs to be trained, and finally achieve the purpose of unsupervised learning. Error back propagation algorithm, is loaded into the convolution neural network algorithm, modify the threshold and weights of neural network to reduce the error of the model. In the classifier, the support vector machine that is added to optimize the classification function of the convolution neural network to improve the validity and robustness of the whole model.

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Titel: Hand gesture recognition based on convolution neural network
verfasst von: Gongfa Li
Heng Tang
Ying Sun
Jianyi Kong
Guozhang Jiang
Du Jiang
Bo Tao
Shuang Xu
Honghai Liu
Publikationsdatum: 29.12.2017
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe Sonderheft 2/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-017-1435-x

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