Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 11
3466-3471

Multi-scale aerial image target detection algorithm based on pro-YOLOv4

Zhao Yuqinga,b,c
Jia Jinlua,b,c
Gong Weijuna,b,c,d
Qian Yuronga,b,c
a. College of Software, b. Key Laboratory of Signal Detection & Processing Autonomous Region, c. Key Laboratory of Software Engineering, d. College of Information Science & Engineering, Xinjiang University, Urumqi 830046, China
DOI: 10.19734/j.issn.1001-3695.2021.01.0068

Abstract

Aerial image target detection has problems such as low accuracy of multi-scale target detection, slow detection speed, serious missed detection and serious misdetection. To solve this problems, this paper proposed a target detection algorithm(pro-YOLOv4) that combined convolutional attention mechanism and lightweight network, and applied it to multi-scale aerial image target detection. First, the algorithm used the K-means clustering algorithm to cluster the aerial data set and optimize the anchor frame parameters, and improved the effectiveness of target detection. Secondly, the algorithm used a lightweight network structure to simplify network complexity and improve detection speed. Finally, the algorithm introduced a convolutional attention module to solve the interference of complex scenes on aerial target detection, thereby effectively reducing the false detection rate and missed detection rate. This algorithm was compared with the aerial photography dataset RSOD and NWPU VHR-10. The experimental results show that the detection effect of pro-YOLOv4 is significantly improved compared with YOLOv4, and the average detection accuracy is increased by 3.42% and 3.98%, respectively. This algorithm not only shows good detection performance for multi-scale targets, but also reduces the missed detection rate of targets, and has good robustness and generalization ability.

Foundation Support

国家自然科学基金资助项目(61966035)
新疆维吾尔自治区研究生创新项目(XJ2020G074)
国家自然科学基金联合基金重点项目(U1803261)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.01.0068
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 11
Section: Technology of Graphic & Image
Pages: 3466-3471
Serial Number: 1001-3695(2021)11-047-3466-06

Publish History

[2021-11-05] Printed Article

Cite This Article

赵玉卿, 贾金露, 公维军, 等. 基于pro-YOLOv4的多尺度航拍图像目标检测算法 [J]. 计算机应用研究, 2021, 38 (11): 3466-3471. (Zhao Yuqing, Jia Jinlu, Gong Weijun, et al. Multi-scale aerial image target detection algorithm based on pro-YOLOv4 [J]. Application Research of Computers, 2021, 38 (11): 3466-3471. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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