Real- Time Detecting and Tracking of Squids Using YOLOv5

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Big Data Pub Date : 2023-08-03 DOI:10.1109/icABCD59051.2023.10220521

Luxolo Kuhlane, Dane Brown, Marc Marais

引用次数: 0

Abstract

This paper proposes a real-time system for detecting and tracking squids using the YOLOv5 object detection algorithm. The system utilizes a large dataset of annotated squid images and videos to train a YOLOv5 model optimized for detecting and tracking squids. The model is fine-tuned to minimize false positives and optimize detection accuracy. The system is deployed on a GPU-enabled device for real-time processing of video streams and tracking of detected squids across frames. The accuracy and speed of the system make it a valuable tool for marine scientists, conservationists, and fishermen to better understand the behavior and distribution of these elusive creatures. Future work includes incorporating additional computer vision techniques and sensor data to improve tracking accuracy and robustness.

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基于YOLOv5的鱿鱼实时检测与跟踪

本文提出了一种基于YOLOv5目标检测算法的实时乌贼检测与跟踪系统。该系统利用大量带注释的鱿鱼图像和视频数据集来训练一个优化的YOLOv5模型，用于检测和跟踪鱿鱼。该模型经过微调，以最大限度地减少误报和优化检测精度。该系统部署在支持gpu的设备上，用于实时处理视频流和跨帧跟踪检测到的鱿鱼。该系统的准确性和速度使其成为海洋科学家、自然资源保护主义者和渔民更好地了解这些难以捉摸的生物的行为和分布的宝贵工具。未来的工作包括结合额外的计算机视觉技术和传感器数据，以提高跟踪精度和鲁棒性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.