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Loess Landslide Detection Using Object Detection Algorithms in Northwest China 期刊论文
REMOTE SENSING, 2022, 卷号: 14, 期号: 5
作者:  Ju, Yuanzhen;  Xu, Qiang;  Jin, Shichao;  Li, Weile;  Su, Yanjun;  Dong, Xiujun;  Guo, Qinghua
Adobe PDF(11451Kb)  |  收藏  |  浏览/下载：9/0  |  提交时间：2024/03/07
loess landslide  google earth image  deep learning  automatic identification  object detection  
A handheld device for measuring the diameter at breast height of individual trees using laser ranging and deep-learning based image recognition 期刊论文
PLANT METHODS, 2021, 卷号: 17, 期号: 1
作者:  Song, Chuangye;  Yang, Bin;  Zhang, Lin;  Wu, Dongxiu
Adobe PDF(1693Kb)  |  收藏  |  浏览/下载：91/1  |  提交时间：2023/02/24
Forest inventory  Tree measurement  Digital camera  Convolutional neural networks  Spatial attention module  
UAV-lidar aids automatic intelligent powerline inspection 期刊论文
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 卷号: 130
作者:  Guan, Hongcan;  Sun, Xiliang;  Su, Yanjun;  Hu, Tianyu;  Wang, Haitao;  Wang, Heping;  Peng, Chigang;  Guo, Qinghua
Adobe PDF(10491Kb)  |  收藏  |  浏览/下载：75/0  |  提交时间：2023/02/24
Powerline inspection  Intelligent  Unmanned aerial vehicle  Deep learning  Lidar  
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
作者:  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)  |  收藏  |  浏览/下载：127/0  |  提交时间：2022/03/01
Classification  deep learning  LiDAR  phenotype  segmentation  structural components  
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
作者:  Xu, Shiwu;  Zhang, Shihui;  Zeng, Jue;  Li, Tingyu;  Guo, Qinghua;  Jin, Shichao
Adobe PDF(6559Kb)  |  收藏  |  浏览/下载：88/0  |  提交时间：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
作者:  Hou, Yemao;  Cui, Xindong;  Canul-Ku, Mario;  Jin, Shichao;  Hasimoto-Beltran, Rogelio;  Guo, Qinghua;  Zhu, Min
Adobe PDF(1648Kb)  |  收藏  |  浏览/下载：88/0  |  提交时间：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  
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
作者:  Yang, Zongfeng;  Gao, Shang;  Xiao, Feng;  Li, Ganghua;  Ding, Yangfeng;  Guo, Qinghua;  Paul, Matthew J.;  Liu, Zhenghui
Adobe PDF(4429Kb)  |  收藏  |  浏览/下载：89/0  |  提交时间：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
作者:  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)  |  收藏  |  浏览/下载：87/0  |  提交时间：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
作者:  Jin, Shichao;  Sun, Yanjun;  Zhao, Xiaoqian;  Hu, Tianyu;  Guo, Qinghua
Adobe PDF(7633Kb)  |  收藏  |  浏览/下载：82/0  |  提交时间：2022/03/01
Digital terrain model (DTM)  deep learning  fully convolutional neural network (FCN)  ground filtering  light detection and ranging (LiDAR)  
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
作者:  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)  |  收藏  |  浏览/下载：97/0  |  提交时间：2022/03/01
Ecological resources  Deep learning  Neural network  Big data  Theory and tools  Application and challenge