A Deep Learning Track Correlation Method

被引：0
作者：
Cui Y.-Q. [1 ]
He Y. [1 ]
Tang T.-T. [1 ]
Xiong W. [1 ]
机构：
[1] Institute of Information Fusion, Naval Aeronautical University, Yantai
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2022年 / 50卷 / 03期
关键词：
Convolutional neural network; Deep learning; Machine learning; Multilayer neural network; Track correlation;
D O I：
10.12263/DZXB.20200299
中图分类号：
学科分类号：
摘要：
According to the theories and methods in machine learning, we converted the track correlation problem in the field of information fusion to a classification recognition problem in the field of machine learning by designing the input data and output data. In advance, a deep learning track correlation method was proposed in this paper. The experiments illustrate that the new method is better than the compared methods in the aspect of correlation performance and adaptation abilities. Thus, the new method would have a good applied foreground. © 2022, Chinese Institute of Electronics. All right reserved.
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页码：759 / 763
页数：4
相关论文
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