Real-time object detection and tracking using YOLOv3 network by quadcopter-Reference-Cited by-同舟云学术

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Real-time object detection and tracking using YOLOv3 network by quadcopter

Published:2023-01-02 Issue: Volume: Page:1-19
ISSN:1539-7734
Container-title:Mechanics Based Design of Structures and Machines
language:en
Short-container-title:Mechanics Based Design of Structures and Machines

Author:

Mokhtari Mir Abolfazl¹,Taheri Mehrdad²

Affiliation:

1. Imam Ali, University, Tehran, Iran

2. Amirkabir, University, Tehran, Iran

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,Ocean Engineering,Condensed Matter Physics,Aerospace Engineering,Automotive Engineering,General Mathematics,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15397734.2022.2162078

Reference18 articles.

1. Wireless vision-based fuzzy controllers for moving object tracking using a quadcopter

2. Benjdira, B., and T. Khursheed. 2019. Car detection using unmanned aerial vehicles: Comparison between faster r-cnn and YOLOv3. 1st International Conference on Unmanned Vehicle Systems-Oman (UVS), 1–6.

3. An autonomous vision-based target tracking system for rotorcraft unmanned aerial vehicles

4. Vision-based target tracking and autonomous landing of a quadrotor on a ground vehicle

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic Modeling of Quadrotor-Slung-Load System: A Model Based on the Quasi-Coordinates Approach;SAE Technical Paper Series;2024-04-09

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