Real-Time Object Detection and Robotic Manipulation for Agriculture Using a YOLO-Based Learning Approach-Reference-Cited by-同舟云学术

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Real-Time Object Detection and Robotic Manipulation for Agriculture Using a YOLO-Based Learning Approach

Published:2024-03-25 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 IEEE International Conference on Industrial Technology (ICIT)
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Author:

Zhao Hongyu¹,Tang Zezhi²,Li Zhenhong³,Dong Yi⁴,Si Yuancheng⁵,Lu Mingyang⁶,Panoutsos George²

Affiliation:

1. Imperial College,The Department of Physics,London,United Kingdom

2. University of Sheffield,The Department of Automatic Control and Systems Engineering,Sheffield,United Kingdom,S1 3JD

3. University of Manchester,The Department of Electrical and Electronic Engineering,Manchester,United Kingdom

4. University of Southampton,The Department of Electronics and Computer Science,Southampton,United Kingdom

5. Fudan University,The Department of Economics,Shanghai,China,200433

6. Iowa State University,The Center for Nondestructive Evaluation (CNDE),Ames,IA,United States,50011

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10540646/10540608/10540740.pdf?arnumber=10540740

Reference22 articles.

1. Harvest mechanization helps agriculture remain competitive

2. Adaptive Affine Formation Maneuver Control of Second-Order Multi-Agent Systems with Disturbances

3. Agricultural robots for field operations: Concepts and components

4. Review in Industrial Automation

5. Unmatched disturbance rejection for AMB systems via DOBC approach

Cited by 2 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. Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI;Scientific Reports;2024-07-06

2. Reinforcement Learning-Based Output Stabilization Control for Nonlinear Systems With Generalized Disturbances;2024 IEEE International Conference on Industrial Technology (ICIT);2024-03-25

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