Water Column Detection Method at Impact Point Based on Improved YOLOv4 Algorithm

Jiaowei Shi, Shiyan Sun, Zhangsong Shi (), Chaobing Zheng and Bo She
Additional contact information
Jiaowei Shi: Weapon Engineering College, Naval University of Engineering, Wuhan 430034, China
Shiyan Sun: Weapon Engineering College, Naval University of Engineering, Wuhan 430034, China
Zhangsong Shi: Weapon Engineering College, Naval University of Engineering, Wuhan 430034, China
Chaobing Zheng: School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Bo She: Weapon Engineering College, Naval University of Engineering, Wuhan 430034, China

Sustainability, 2022, vol. 14, issue 22, 1-15

Abstract: For a long time, the water column at the impact point of a naval gun firing at the sea has mainly depended on manual detection methods for locating, which has problems such as low accuracy, subjectivity and inefficiency. In order to solve the above problems, this paper proposes a water column detection method based on an improved you-only-look-once version 4 (YOLOv4) algorithm. Firstly, the method detects the sea antenna through the Hoffman line detection method to constrain the sensitive area in the current detection image so as to improve the accuracy of water column detection; secondly, density-based spatial clustering of applications with noise (DBSCAN) + K-means clustering algorithm is used to obtain a better prior bounding box, which is input into the YOLOv4 network to improve the positioning accuracy of the water column; finally, the convolutional block attention module (CBAM) is added in the PANet structure to improve the detection accuracy of the water column. The experimental results show that the above algorithm can effectively improve the detection accuracy and positioning accuracy of the water column at the impact point.

Keywords: YOLOv4; Hoffman line detection; DBSCAN cluster algorithm; K-means cluster algorithm; CBMA; water column detection (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/22/15329/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/22/15329/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:22:p:15329-:d:976759

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().