北京水务Issue(2)：66-72,7.DOI:10.19671/j.1673-4637.2024.02.012
联合上下文注意力机制的水位检测算法分析
Water level detection algorithm featured by a context attention mechanism
丁晓嵘 1耿艳兵2
作者信息
- 1. 北京市智慧水务发展研究院 北京 100036
- 2. 中北大学计算机科学与技术学院 山西 太原 030051
- 折叠
摘要
Abstract
Intelligent monitoring of water level plays a crucial role in timely water resource management and disaster prevention.To tackle challenges like varying shooting perspectives,adverse weather condi-tions,and water pollution,a water level detection algorithm incorporating a joint context attention mecha-nism was proposed.This algorithm,based on the context attention mechanism of the UNet model(CAM-UNet)and the least squares polynomial fitting function,facilitated intelligent remote acquisition of water level information into intricate backgrounds.The research results demonstrated that the proposed algo-rithm could accurately segment water level lines even with amidst disturbances,such as misaligned cam-era installation,lens jitter and dirty water surfaces,the proposed algorithm accurately segmented the wa-ter level line.It achieved accurate without relying on water gauges by mapping the height deviations of wa-ter level pixels to real-world elevations,ensuring measurement assurance rates and maximum deviations in compliance with"Water Level Observation Standards".These research findings will hold significant ap-plication value in addressing the challenges of real-time precise water level detection as well as flood warning in complex monitoring scenarios.关键词
水位检测/上下文注意力/UNet模型/最小二乘多项式Key words
water level detection/context attention/UNet model/least square by using polynomials分类
通用工业技术引用本文复制引用
丁晓嵘,耿艳兵..联合上下文注意力机制的水位检测算法分析[J].北京水务,2024,(2):66-72,7.
