Survey of UAV Visual tracking Technology based on Convolutional Neural Networks

Yage Xie

doi:10.47297/taposatWSP2633-456928.20250609

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Survey of UAV Visual tracking Technology based on Convolutional Neural Networks

6卷第9期

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Survey of UAV Visual tracking Technology based on Convolutional Neural Networks
Survey of UAV Visual tracking Technology based on Convolutional Neural Networks
Zhengzhou University of Light Industry, Zhengzhou, Henan, 450000, China
2025年6卷第9期页码：141-144
纸质出版：2025-09-30
DOI：10.47297/taposatWSP2633-456928.20250609
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Yage Xie. (2025). Survey of UAV Visual tracking Technology based on Convolutional Neural Networks. 科技理论与实践（英文版）, 6(9), 141-144.

Xie Yage.Survey of UAV Visual tracking Technology based on Convolutional Neural Networks[J].Theory and Practice of Science and Technology,2025,06(09):141-144.
Yage Xie. (2025). Survey of UAV Visual tracking Technology based on Convolutional Neural Networks. 科技理论与实践（英文版）, 6(9), 141-144. DOI： 10.47297/taposatWSP2633-456928.20250609.

Xie Yage.Survey of UAV Visual tracking Technology based on Convolutional Neural Networks[J].Theory and Practice of Science and Technology,2025,06(09):141-144. DOI： 10.47297/taposatWSP2633-456928.20250609.

摘要

Abstract

In this paper

the unmanned aerial vehicle (UAV) based on convolution neural network visual tracking technology has carried on the comprehensive review

including its development course

research status and development trend in the future. Through combing and analyzing therelevant literature

the advantages and disadvantages of different algorithms in UAV visual tracking are summarized

and some research directions worthy of in-depth discussion are proposed. This paper also summarizes and analyzes the current challenges and problems

and discusses how to further improve the performance and stability of UAV visual tracking technology. Finally

the application prospect of UAV visual tracking technology in military and civilian fields is prospected

which provides reference and inspiration for related research and development work.

关键词

Keywords

references

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Wang Xianhao. Research on pedestrian detection and multi-target tracking algorithm based on convolutional neural Network [D]. Chongqing University of Posts and Telecommunications,2021.

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