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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
Adobe PDF(14928Kb)
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Submit date:2022/03/01
Classification
deep learning
LiDAR
phenotype
segmentation
structural components
Application of deep learning in ecological resource research: Theories, methods, and challenges
期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2020, 卷号: 63, 期号: 10, 页码: 1457-1474
Authors:
Guo, Qinghua
;
Jin, Shichao
;
Li, Min
;
Yang, Qiuli
;
Xu, Kexin
;
Ju, Yuanzhen
;
Zhang, Jing
;
Xuan, Jing
;
Liu, Jin
;
Su, Yanjun
;
Xu, Qiang
;
Liu, Yu
Adobe PDF(4690Kb)
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Submit date:2022/03/01
Ecological resources
Deep learning
Neural network
Big data
Theory and tools
Application and challenge
A Framework for Land Use Scenes Classification Based on Landscape Photos
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 卷号: 13, 页码: 6124-6141
Authors:
Xu, Shiwu
;
Zhang, Shihui
;
Zeng, Jue
;
Li, Tingyu
;
Guo, Qinghua
;
Jin, Shichao
Adobe PDF(6559Kb)
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Submit date:2022/03/01
Semantics
Remote sensing
Image analysis
Image segmentation
Object recognition
Machine learning
Forestry
Deep convolutional neural networks (DCNNs)
landscape photos
land survey
land use scene classification
ADMorph: A 3D Digital Microfossil Morphology Dataset for Deep Learning
期刊论文
IEEE ACCESS, 2020, 卷号: 8, 页码: 148744-148756
Authors:
Hou, Yemao
;
Cui, Xindong
;
Canul-Ku, Mario
;
Jin, Shichao
;
Hasimoto-Beltran, Rogelio
;
Guo, Qinghua
;
Zhu, Min
Adobe PDF(1648Kb)
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Submit date:2022/03/01
Three-dimensional displays
Solid modeling
Computational modeling
Machine learning
Two dimensional displays
Biological system modeling
Shape
Archives of digital morphology
data preprocessing
feature extraction
3D microfossil model classification
deep learning
Estimating Ecosystem Respiration in the Grasslands of Northern China Using Machine Learning: Model Evaluation and Comparison
期刊论文
SUSTAINABILITY, 2020, 卷号: 12, 期号: 5
Authors:
Zhu, Xiaobo
;
He, Honglin
;
Ma, Mingguo
;
Ren, Xiaoli
;
Zhang, Li
;
Zhang, Fawei
;
Li, Yingnian
;
Shi, Peili
;
Chen, Shiping
;
Wang, Yanfen
;
Xin, Xiaoping
;
Ma, Yaoming
;
Zhang, Yu
;
Du, Mingyuan
;
Ge, Rong
;
Zeng, Na
;
Li, Pan
;
Niu, Zhongen
;
Zhang, Liyun
;
Lv, Yan
;
Song, Zengjing
;
Gu, Qing
Adobe PDF(1290Kb)
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Submit date:2022/03/01
ecosystem respiration
machine learning
deep learning
grasslands
northern China
Leaf to panicle ratio (LPR): a new physiological trait indicative of source and sink relation in japonica rice based on deep learning
期刊论文
PLANT METHODS, 2020, 卷号: 16, 期号: 1
Authors:
Yang, Zongfeng
;
Gao, Shang
;
Xiao, Feng
;
Li, Ganghua
;
Ding, Yangfeng
;
Guo, Qinghua
;
Paul, Matthew J.
;
Liu, Zhenghui
Adobe PDF(4429Kb)
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View/Download:6/0
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Submit date:2022/03/01
Plant phenotyping
Leaf and panicle detection
Deep learning
Physiological trait
Leaf to panicle ratio (LPR)
Japonica rice
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)
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View/Download:6/0
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Submit date:2022/03/01
Biomass
Phenotype
Machine learning
Terrestrial lidar
Precision agriculture
A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 卷号: 13, 页码: 3958-3974
Authors:
Jin, Shichao
;
Sun, Yanjun
;
Zhao, Xiaoqian
;
Hu, Tianyu
;
Guo, Qinghua
Adobe PDF(7633Kb)
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View/Download:5/0
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Submit date:2022/03/01
Digital terrain model (DTM)
deep learning
fully convolutional neural network (FCN)
ground filtering
light detection and ranging (LiDAR)
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)
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Submit date:2022/02/25
deep learning
detection
classification
segmentation
phenotype
Lidar (light detection and ranging)
The permafrost carbon inventory on the Tibetan Plateau: a new evaluation using deep sediment cores
期刊论文
GLOBAL CHANGE BIOLOGY, 2016, 卷号: 22, 期号: 8, 页码: 2688-2701
Authors:
Ding JZ
;
Li F
;
Yang GB
;
Chen LY
;
Zhang BB
;
Liu L
;
Fang K
;
Qin SQ
;
Chen YL
;
Peng YF
;
Ji CJ
;
He HL
;
Smith P
;
Yang YH
Adobe PDF(1031Kb)
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Submit date:2018/12/07