期刊名称：Journal of Intelligent Learning Systems and Applications
印刷版ISSN：2150-8402
电子版ISSN：2150-8410
出版年度：2012
卷号：4
期号：1
页码：41-52
DOI：10.4236/jilsa.2012.41004
出版社：Scientific Research Publishing
摘要：The objective of this research is to introduce the use of different types of neural networks in human hand gesture recognition for static images as well as for dynamic gestures. This work focuses on the ability of neural networks to assist in Arabic Sign Language (ArSL) hand gesture recognition. We have presented the use of feedforward neural networks and recurrent neural networks along with its different architectures; partially and fully recurrent networks. Then we have tested our proposed system; the results of the experiment have showed that the suggested system with the fully recurrent architecture has had a performance with an accuracy rate 95% for static gesture recognition.
