期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2021
卷号：48
期号：4
语种：English
出版社：IAENG - International Association of Engineers
摘要：Hand gesture is a communication tool that allows messages to be conveyed, actions to be performed through hand gestures. Hence, it has the ability to simplify communication and enhance human computer interaction. This paper proposed Wide Residual Network for static hand gesture recognition. WRN improves feature propagation and gradient flows by utilizing shortcut connection in residual block. Wide residual block further improves upon residual block by increasing the width of the network and improving feature reuse, and thereby allowing the depth of the network to be trimmed and fewer trainable parameters to be learned. The network is experimented on three public datasets and compared with existing convolutional neural network (CNN) variants proposed for static hand gesture recognition. Experimental results show Wide Residual Network outperforms the existing CNN variants proposed for hand gesture recognition.
关键词：Hand gesture recognition;Sign language recognition;Convolutional Neural Network (CNN);Wide Residual Network
