论文标题
一个新的数据集和拟议的卷积神经网络体系结构，用于分类美国手语数字
A New Dataset and Proposed Convolutional Neural Network Architecture for Classification of American Sign Language Digits
论文作者
论文摘要
根据与与言语障碍者一起工作的人的采访，言语受损的人很难与周围的其他人交流，这些人不知道手语，这种情况可能会导致他们孤立自己与社会隔离并失去独立感。在本文中，为了提高个人使用手语和不了解这种语言的个人之间的沟通的个人的生活质量呈现数据集并与现有流行的CNN模型进行了比较。
According to interviews with people who work with speech impaired persons, speech impaired people have difficulties in communicating with other people around them who do not know the sign language, and this situation may cause them to isolate themselves from society and lose their sense of independence. With this paper, to increase the quality of life of individuals with facilitating communication between individuals who use sign language and who do not know this language, a new American Sign Language (ASL) digits dataset that can help to create machine learning algorithms which need to large and varied data to be successful created and published as Sign Language Digits Dataset on Kaggle Datasets web page, a proposal Convolutional Neural Network (CNN) architecture that can get 98% test accuracy on our dataset presented, and compared with the existing popular CNN models.
