中文版 | English

在结果中检索

IB-CAS

浏览/检索结果: 共6条，第1-6条 帮助

限定条件            
已选(0)清除 条数/页：   排序方式：
Deciphering the contributions of spectral and structural data to wheat yield estimation from proximal sensing 期刊论文
CROP JOURNAL, 2022, 卷号: 10, 期号: 5, 页码: 1334-1345
作者:  Li, Qing;  Jin, Shichao;  Zang, Jingrong;  Wang, Xiao;  Sun, Zhuangzhuang;  Li, Ziyu;  Xu, Shan;  Ma, Qin;  Su, Yanjun;  Guo, Qinghua;  Jiang, Dong
Adobe PDF(3253Kb)  |  收藏  |  浏览/下载：9/0  |  提交时间：2024/03/07
LiDAR  Multispectral  Yield  Phenotype  Hyper-temporal  
Allometry-based estimation of forest aboveground biomass combining LiDAR canopy height attributes and optical spectral indexes 期刊论文
FOREST ECOSYSTEMS, 2022, 卷号: 9
作者:  Yang, Qiuli;  Su, Yanjun;  Hu, Tianyu;  Jin, Shichao;  Liu, Xiaoqiang;  Niu, Chunyue;  Liu, Zhonghua;  Kelly, Maggi;  Wei, Jianxin;  Guo, Qinghua
Adobe PDF(4150Kb)  |  收藏  |  浏览/下载：13/0  |  提交时间：2024/03/07
Forest aboveground biomass  Drone LiDAR  Allometric relationship  Power law  Tree height  Vegetation index  
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：89/0  |  提交时间：2022/03/01
Biomass  Phenotype  Machine learning  Terrestrial lidar  Precision agriculture  
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：105/0  |  提交时间：2022/03/01
Ecological resources  Deep learning  Neural network  Big data  Theory and tools  Application and challenge  
Estimation of degraded grassland aboveground biomass using machine learning methods from terrestrial laser scanning data 期刊论文
ECOLOGICAL INDICATORS, 2020, 卷号: 108
作者:  Xu, Kexin;  Su, Yanjun;  Liu, Jin;  Hu, Tianyu;  Jin, Shichao;  Ma, Qin;  Zhai, Qiuping;  Wang, Rui;  Zhang, Jing;  Li, Yumei;  Liu, Hon An;  Guo, Qinghua
Adobe PDF(4794Kb)  |  收藏  |  浏览/下载：93/0  |  提交时间：2022/03/01
Aboveground biomass (AGB)  Degraded grassland  Machine learning  Northern agro-pastoral ecotone  Terrestrial laser scanning (TLS)  
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
作者:  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)  |  收藏  |  浏览/下载：77/0  |  提交时间：2022/02/25
deep learning  detection  classification  segmentation  phenotype  Lidar (light detection and ranging)