计算机与数字工程2024，Vol.52Issue(3)：915-921,7.DOI:10.3969/j.issn.1672-9722.2024.03.047
基于YOLOv5-SSA的水炮射击半遮挡目标检测
Semi-obstructed Object Detection in Water Cannon Shooting Based on YOLOv5-SSA
向河汉 1陈黎 1陈姚节1
作者信息
- 1. 武汉科技大学智能信息处理与实时工业系统湖北省重点实验室 武汉 430081
- 折叠
摘要
Abstract
When the ship's water cannon is shooting target,it is easy to produce splashes,which can block the shooting tar-get.The existing water cannon control and tracking system is easy to lose the target in the water cannon shooting scene,and it is dif-ficult to obtain an effective aiming effect.This paper proposes an object detection method based on deep learning,which takes the image taken during the shooting of the water cannon as input,and detects the position of the target to be shot in real time to correct the effect of object tracking and achieve accurate and effective shooting of the target.In this paper,a lightweight deep learning ob-ject detection network YOLOv5-SSA is designed to detect targets fired by water cannons in real-time.When tested in actual scenes,the processing speed reaches 21.18ms under the premise that the object detection precision reaches 93.2%,and it achieves real-time detection of the target.关键词
目标检测/实时/深度学习/水炮Key words
object detection/real-time/deep learning/water cannon分类
军事科技引用本文复制引用
向河汉,陈黎,陈姚节..基于YOLOv5-SSA的水炮射击半遮挡目标检测[J].计算机与数字工程,2024,52(3):915-921,7.
