Gesture recognition based on improved VGGNET convolutional neural network

被引：0
|
作者：
Yang Zhiqi [1 ]
机构：
[1] Tianjin Univ, Renai Coll, Dept Comp Sci & Technol, Tianjin 301636, Peoples R China
来源：
PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020) | 2020年
关键词：
VGGNet; GoogLeNet; TensorFlow; deep learning; convolutional neural network;
D O I：
10.1109/itoec49072.2020.9141803
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, based on the problem that the existing deep learning neural network relies on large-scale training data and powerful computing power, the convolutional neural network VGGNet is improved, and a modified gesture recognition algorithm based on VGGNet is proposed. Experiments show that under the condition of small training data size and limited computing power, the improved convolutional neural network algorithm has higher recognition rate and can meet the requirements of practical gesture recognition applications.
引用
收藏
页码：1736 / 1739
页数：4
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