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arxiv logo>cs> arXiv:2404.06883
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Computer Science > Computer Vision and Pattern Recognition

arXiv:2404.06883 (cs)
[Submitted on 10 Apr 2024 (v1), last revised 19 Apr 2024 (this version, v2)]

Title:Research on Detection of Floating Objects in River and Lake Based on AI Intelligent Image Recognition

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Abstract:With the rapid advancement of artificial intelligence technology, AI-enabled image recognition has emerged as a potent tool for addressing challenges in traditional environmental monitoring. This study focuses on the detection of floating objects in river and lake environments, exploring an innovative approach based on deep learning. By intricately analyzing the technical pathways for detecting static and dynamic features and considering the characteristics of river and lake debris, a comprehensive image acquisition and processing workflow has been developed. The study highlights the application and performance comparison of three mainstream deep learning models -SSD, Faster-RCNN, and YOLOv5- in debris identification. Additionally, a detection system for floating objects has been designed and implemented, encompassing both hardware platform construction and software framework development. Through rigorous experimental validation, the proposed system has demonstrated its ability to significantly enhance the accuracy and efficiency of debris detection, thus offering a new technological avenue for water quality monitoring in rivers and lakes
Subjects:Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI)
Cite as:arXiv:2404.06883 [cs.CV]
 (orarXiv:2404.06883v2 [cs.CV] for this version)
 https://doi.org/10.48550/arXiv.2404.06883
arXiv-issued DOI via DataCite

Submission history

From: Ao Xiang [view email]
[v1] Wed, 10 Apr 2024 10:13:37 UTC (775 KB)
[v2] Fri, 19 Apr 2024 06:07:22 UTC (696 KB)
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