基于注意卷积网络的数字识别系统手势虚拟素描

Elsen Ronando, Putri Rahayu Ningtiyas
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引用次数: 0

摘要

现代计算机技术的发展日新月异。计算机技术对人类生活产生了重大影响。人与计算机之间的关系,被称为人机交互(HCI),可以进行非接触或虚拟;一个例子是手势识别。然而,手势识别的发展面临着一些挑战,特别是在提高其荣耀性能方面。目前有几种方法可以提高手势识别的性能,如卷积神经网络,但仍有待改进。在本文中,我们使用注意卷积网络进行了一个基于数字识别系统的带有手势的虚拟素描,在非实时中获得的准确率值为83.9%,实时准确率为90%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Number Recognition System-based Virtual Sketch with Hand Gestures Using Attentional Convolutional Network
Advances in computer technology in the modern era have proliferated. Computer technology has had a significant impact on human life. The relationship between humans and computers, known as Human-Computer Interactions (HCI), can be done non-contact or virtual; one example is Hand Gesture Recognition. However, the development of hand gesture recognition has several challenges, especially in increasing the performance of its glory. Several methods are used to improve the performance of hand gesture recognition, such as the convolutional neural network, which still needs improvement. In this paper, we conducted a number recognition system-based virtual sketch with a hand gesture using an Attentional Convolutional Network with an accuracy value obtained in the non-real-time of 83.9% and real-time accuracy is 90%.
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