White Mold and Weed Detection in Snap Beans Using UAS-Based Lidar-Reference-Cited by-同舟云学术

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White Mold and Weed Detection in Snap Beans Using UAS-Based Lidar

Published:2022-07-17 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Zhang Fei¹,Hassanzadeh Amirhossein¹,Kikkert Julie²,Pethybridge Sarah Jane³,Aardt Jan van¹

Affiliation:

1. Rochester Institute of Technology,Chester F. Carlson Center for Imaging Science,Rochester,NY,USA,14623

2. Cornell Cooperative Extension,Canandaigua,NY,USA,14424

3. Cornell AgriTech,Plant Pathology & Plant Microbe Biology Section,Geneva,NY,USA,14456

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9883023/9883024/09883927.pdf?arnumber=9883927

Reference14 articles.

1. Automatic Classification of Cotton Root Rot Disease Based on UAV Remote Sensing

2. Crop height determination with UAS point clouds

3. Comparison of UAS-Based Structure-from-Motion and LiDAR for Structural Characterization of Short Broadacre Crops

4. Evaluation of Leaf Area Index (LAI) of Broadacre Crops Using UAS-Based LiDAR Point Clouds and Multispectral Imagery

5. Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z)

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. Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques;Computers and Electronics in Agriculture;2024-07

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