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Separating the Structural Components of Maize for Field Phenotyping Using Terrestrial LiDAR Data and Deep Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 卷号: 58, 期号: 4, 页码: 2644-2658
Authors:  Jin, Shichao;  Su, Yanjun;  Gao, Shang;  Wu, Fangfang;  Ma, Qin;  Xu, Kexin;  Hu, Tianyu;  Liu, Jin;  Pang, Shuxin;  Guan, Hongcan;  Zhang, Jing;  Guo, Qinghua
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Classification  deep learning  LiDAR  phenotype  segmentation  structural components  
Non-destructive estimation of field maize biomass using terrestrial lidar: an evaluation from plot level to individual leaf level 期刊论文
PLANT METHODS, 2020, 卷号: 16, 期号: 1
Authors:  Jin, Shichao;  Su, Yanjun;  Song, Shilin;  Xu, Kexin;  Hu, Tianyu;  Yang, Qiuli;  Wu, Fangfang;  Xu, Guangcai;  Ma, Qin;  Guan, Hongcan;  Pang, Shuxin;  Li, Yumei;  Guo, Qinghua
Adobe PDF(4774Kb)  |  Favorite  |  View/Download：6/0  |  Submit date：2022/03/01
Biomass  Phenotype  Machine learning  Terrestrial lidar  Precision agriculture  
Evaluating maize phenotype dynamics under drought stress using terrestrial lidar 期刊论文
PLANT METHODS, 2019, 卷号: 15
Authors:  Su, Yanjun;  Wu, Fangfang;  Ao, Zurui;  Jin, Shichao;  Qin, Feng;  Liu, Boxin;  Pang, Shuxin;  Liu, Lingli;  Guo, Qinghua
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Maize  Phenotype  Lidar  Drought stress  
Stem-Leaf Segmentation and Phenotypic Trait Extraction of Individual Maize Using Terrestrial LiDAR Data 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 卷号: 57, 期号: 3, 页码: 1336-1346
Authors:  Jin, Shichao;  Su, Yanjun;  Wu, Fangfang;  Pang, Shuxin;  Gao, Shang;  Hu, Tianyu;  Liu, Jin;  Guo, Qinghua
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Light detection and ranging (LiDAR)  phenotypic traits  regional growth  segmentation  skeleton  
Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping 期刊论文
SCIENCE CHINA-LIFE SCIENCES, 2018, 卷号: 61, 期号: 3, 页码: 328-339
Authors:  Guo, Qinghua;  Wu, Fangfang;  Pang, Shuxin;  Zhao, Xiaoqian;  Chen, Linhai;  Liu, Jin;  Xue, Baolin;  Xu, Guangcai;  Li, Le;  Jing, Haichun;  Chu, Chengcai
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crop breeding  phenotypic traits  data fusion  LiDAR  high-throughput  integrated platform  
Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms 期刊论文
FRONTIERS IN PLANT SCIENCE, 2018, 卷号: 9
Authors:  Jin, Shichao;  Su, Yanjun;  Gao, Shang;  Wu, Fangfang;  Hu, Tianyu;  Liu, Jin;  Li, Wankai;  Wang, Dingchang;  Chen, Shaojiang;  Jiang, Yuanxi;  Pang, Shuxin;  Guo, Qinghua
Adobe PDF(2278Kb)  |  Favorite  |  View/Download：5/0  |  Submit date：2022/02/25
deep learning  detection  classification  segmentation  phenotype  Lidar (light detection and ranging)  
An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China 期刊论文
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 卷号: 38, 期号: 8-10, 页码: 2954-2972
Authors:  Guo, Qinghua;  Su, Yanjun;  Hu, Tianyu;  Zhao, Xiaoqian;  Wu, Fangfang;  Li, Yumei;  Liu, Jin;  Chen, Linhai;  Xu, Guangcai;  Lin, Guanghui;  Zheng, Yi;  Lin, Yiqiong;  Mi, Xiangcheng;  Fei, Lin;  Wang, Xugao
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