Spray Drift Segmentation for Intelligent Spraying System Using 3D Point Cloud Deep Learning Framework
Author:
Affiliation:
1. Department of Convergence Biosystems Engineering, Chonnam National University, Buk-gu, Gwangju, Republic of Korea
2. Hyundai Robotics, Yongin-si, Republic of Korea
Funder
Cooperative Research Program or Agriculture Science and Technology Development
Rural Development Administration, Republic of Korea
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09832619.pdf?arnumber=9832619
Reference29 articles.
1. Control of Insects and Diseases with Intelligent Variable-rate Sprayers in Ornamental Nurseries1
2. Design and performance evaluation of a variable-rate orchard sprayer based on a laser-scanning sensor
3. Field evaluations of a deep learning-based intelligent spraying robot with flow control for pear orchards
4. Assessment of spray drift from pesticide applications in soybean crops
5. Spray drift
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