Using Deep Convolutional Networks for Gesture Recognition in American Sign Language
Using Deep Convolutional Networks for Gesture Recognition in American Sign Language
复制标题
使用深度卷积网络进行美国手语手势识别
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Dianna Radpour
中科院分区：
文献类型：
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作者：
Vivek Bheda;Dianna Radpour
在多模式交流领域，手语一直是研究最少的领域之一。随着深度学习领域的最新进展，神经网络对手语翻译具有深远的影响和应用。本文提出了一种利用深卷积网络对美国手语中的字母和数字图像进行分类的方法。
In the realm of multimodal communication, sign language is, and continues to be, one of the most understudied areas. In line with recent advances in the field of deep learning, there are far reaching implications and applications that neural networks can have for sign language interpretation. In this paper, we present a method for using deep convolutional networks to classify images of both the the letters and digits in American Sign Language.