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Research (Washington, D.C.)
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March 23, 2023
Application of Internet of Things to Agriculture-The LQ-FieldPheno Platform: A High-Throughput Platform for Obtaining Crop Phenotypes in Field
Jiangchuan Fan, Yinglun Li, Shuan Yu, et al.
Plant Phenomics (Washington, D.C.)
|
June 27, 2024
Detection and Identification of Tassel States at Different Maize Tasseling Stages Using UAV Imagery and Deep Learning
Jianjun Du, Jinrui Li, Jiangchuan Fan, et al.
Plants (Basel, Switzerland)
|
February 11, 2023
Design and Development of a Low-Cost UGV 3D Phenotyping Platform with Integrated LiDAR and Electric Slide Rail
Shuangze Cai, Wenbo Gou, Weiliang Wen, et al.
Frontiers in Plant Science
|
October 30, 2020
Image-Based High-Throughput Detection and Phenotype Evaluation Method for Multiple Lettuce Varieties
Jianjun Du, Xianju Lu, Jiangchuan Fan, et al.
Frontiers in Plant Science
|
July 18, 2022
Hyperspectral Technique Combined With Deep Learning Algorithm for Prediction of Phenotyping Traits in Lettuce
Shuan Yu, Jiangchuan Fan, Xianju Lu, et al.
Plant Phenomics (Washington, D.C.)
|
December 14, 2020
MVS-Pheno: A Portable and Low-Cost Phenotyping Platform for Maize Shoots Using Multiview Stereo 3D Reconstruction
Sheng Wu, Weiliang Wen, Yongjian Wang, et al.
Frontiers in Plant Science
|
February 23, 2023
A reinterpretation of the gap fraction of tree crowns from the perspectives of computer graphics and porous media theory
Yunfeng Zhu, Dongni Li, Jiangchuan Fan, et al.
Frontiers in Plant Science
|
June 20, 2019
Crop Phenomics: Current Status and Perspectives
Chunjiang Zhao, Ying Zhang, Jianjun Du, et al.
Plant Phenomics (Washington, D.C.)
|
May 24, 2023
Multi-Source Data Fusion Improves Time-Series Phenotype Accuracy in Maize under a Field High-Throughput Phenotyping Platform
Yinglun Li, Weiliang Wen, Jiangchuan Fan, et al.
Plant Phenomics (Washington, D.C.)
|
April 27, 2026
From leaf to canopy: Inversion of lettuce pigment distribution using hyperspectral imaging technology combined with deep learning algorithms
Yue Zhao, Jiangchuan Fan, Xianju Lu, et al.
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Showing results (1-10 of 12) with videos related to
Sort By:
Page
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Research (Washington, D.C.)
|
March 23, 2023
Application of Internet of Things to Agriculture-The LQ-FieldPheno Platform: A High-Throughput Platform for Obtaining Crop Phenotypes in Field
Jiangchuan Fan, Yinglun Li, Shuan Yu, et al.
Plant Phenomics (Washington, D.C.)
|
June 27, 2024
Detection and Identification of Tassel States at Different Maize Tasseling Stages Using UAV Imagery and Deep Learning
Jianjun Du, Jinrui Li, Jiangchuan Fan, et al.
Plants (Basel, Switzerland)
|
February 11, 2023
Design and Development of a Low-Cost UGV 3D Phenotyping Platform with Integrated LiDAR and Electric Slide Rail
Shuangze Cai, Wenbo Gou, Weiliang Wen, et al.
Frontiers in Plant Science
|
October 30, 2020
Image-Based High-Throughput Detection and Phenotype Evaluation Method for Multiple Lettuce Varieties
Jianjun Du, Xianju Lu, Jiangchuan Fan, et al.
Frontiers in Plant Science
|
July 18, 2022
Hyperspectral Technique Combined With Deep Learning Algorithm for Prediction of Phenotyping Traits in Lettuce
Shuan Yu, Jiangchuan Fan, Xianju Lu, et al.
Plant Phenomics (Washington, D.C.)
|
December 14, 2020
MVS-Pheno: A Portable and Low-Cost Phenotyping Platform for Maize Shoots Using Multiview Stereo 3D Reconstruction
Sheng Wu, Weiliang Wen, Yongjian Wang, et al.
Frontiers in Plant Science
|
February 23, 2023
A reinterpretation of the gap fraction of tree crowns from the perspectives of computer graphics and porous media theory
Yunfeng Zhu, Dongni Li, Jiangchuan Fan, et al.
Frontiers in Plant Science
|
June 20, 2019
Crop Phenomics: Current Status and Perspectives
Chunjiang Zhao, Ying Zhang, Jianjun Du, et al.
Plant Phenomics (Washington, D.C.)
|
May 24, 2023
Multi-Source Data Fusion Improves Time-Series Phenotype Accuracy in Maize under a Field High-Throughput Phenotyping Platform
Yinglun Li, Weiliang Wen, Jiangchuan Fan, et al.
Plant Phenomics (Washington, D.C.)
|
April 27, 2026
From leaf to canopy: Inversion of lettuce pigment distribution using hyperspectral imaging technology combined with deep learning algorithms
Yue Zhao, Jiangchuan Fan, Xianju Lu, et al.
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of 2