查询结果:   付优,任芳.基于AE-CNN的手势识别算法[J].计算机应用与软件,2019,36(11):157 - 160,167.
中文标题
基于AE-CNN的手势识别算法
发表栏目
人工智能与识别
摘要点击数
246
英文标题
HAND GESTURE RECOGNITION ALGORITHM BASED ON AE-CNN
作 者
付优 任芳 Fu You Ren Fang
作者单位
山西建筑职业技术学院计算机工程系 山西 晋中 030600 陕西师范大学数学与信息科学学院 陕西 西安 710061    
英文单位
Department of Computer Engineering,Shanxi College of Architectural, Jinzhong 030619, Shanxi, China College of Mathematics and Information Science, Shaanxi Normal University, Xi’an 710061, Shaanxi, China    
关键词
手势识别 卷积神经网络 深度学习
Keywords
Hand gesture recognition Convolutional neural network Deep learning
基金项目
国家自然科学基金项目(61602072)
作者资料
付优,讲师,主研领域:计算机应用技术。任芳,副教授。 。
文章摘要
在手势识别的过程中,手势的多样性和复杂程度会对手势识别率造成很大的影响。随着深度学习的快速发展,卷积神经网络在手势识别领域取得了突破性进展。但基于卷积神经网络的方法仍存在收敛速度慢、识别率低等问题,因此手势识别很难取得较好成果。为了解决卷积神经网络在手势识别中存在的收敛速度慢、识别率低问题,提出一种AE-CNN的手势识别算法。实验结果表明,该算法收敛速度快、识别准确率高,并且没有明显增加识别过程的耗时性。
Abstract
In the process of gesture recognition, the diversity and complexity of gesture greatly influence the recognition rate. With the rapid development of deep learning, the convolution neural network (CNN) has made a breakthrough in the field of gesture recognition. The existing methods based on CNN still have some problems such as slow convergence speed and low recognition rate, so it is difficult to achieve good results in gesture recognition. To solve these problems, this paper proposes an AE-CNN recognition algorithm. The results show that the proposed algorithm has fast convergence speed, high recognition rate, and does not significantly increase the time consumption of the recognition process.
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