海洋开发与管理2024，Vol.41Issue(1)：94-101,8.
基于深度学习的视频观测潮位技术研究
Research on Tidal Level Technology Based on Deep Learning Video Observation:A case study of Xiamen Gaoqi Wharf
摘要
Abstract
Nearshore tidal observation is one of the most fundamental tasks in ocean engineering appli-cations,coastal disaster mitigation,coastal zone management,and ocean-related scientific research.In this paper,a method based on video image deep learning is proposed to extract tidal level features from the video frames captured by a fixed camera installed near the shore,using YOLOv5 visual AI model for tidal analysis.The study used the high-definition camera of Xiamen Gaoqi Wharf with a resolution of 1920× 1080 as the training and validation dataset for the February 2023,and the test dataset for March 2023.The hourly tide data of the coastal tide verification well is used for annotation,and the YOLOv5 object detection model is used for training.The calculation results show that the errors of tidal observation through video on the training set and the test set are 3.9cm and 5.3cm,respectively.One pixel in the video represents 3.8cm,so the average error of the tidal observation is at the pixel lev-el.The study shows that the method of using high-definition cameras based on image deep learning for tidal observation near the shore is feasible,and the observation accuracy depends on the resolution of the target object in the image.关键词
深度学习/潮位观测/厦门高崎码头/高清视频Key words
Deep learning/Tidal level observation/Xiamen Gaoqi Wharf/High definition video分类
海洋科学引用本文复制引用
曾志,陈智杰,孙全..基于深度学习的视频观测潮位技术研究[J].海洋开发与管理,2024,41(1):94-101,8.基金项目
自然资源部第三海洋研究所基本科研业务费专项资金资助项目"不同物源砾石海滩沉积与动力地貌差异性研究"(No.2019029) （No.2019029）
厦门市海洋与渔业发展专项资金青年科技创新项目资助"基于高清视频识别技术的近岸潮汐、海流、波浪观测技术研究"(23ZHZB050QCB40). （23ZHZB050QCB40）
