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One-Class Remote Sensing Classification From Positive and Unlabeled Background Data 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 730-746
作者:  Li, Wenkai;  Guo, Qinghua;  Elkan, Charles
Adobe PDF(11598Kb)  |  收藏  |  浏览/下载：84/0  |  提交时间：2023/02/24
Training  Remote sensing  Classification algorithms  Mathematical model  Support vector machines  Data models  Prediction algorithms  Case-control sampling  labeled and unlabeled data  one-class classification  positive and background learning with constraints (PBLC)  remote sensing  
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：97/0  |  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：103/0  |  提交时间：2022/03/01
Biomass  Phenotype  Machine learning  Terrestrial lidar  Precision agriculture  
One-class remote sensing classification: one-class vs. binary classifiers 期刊论文
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2018, 卷号: 39, 期号: 6, 页码: 1890-1910
作者:  Deng, Xueqing;  Li, Wenkai;  Liu, Xiaoping;  Guo, Qinghua;  Newsam, Shawn
Adobe PDF(7030Kb)  |  收藏  |  浏览/下载：91/0  |  提交时间：2022/02/25
One-Class Classification of Airborne LiDAR Data in Urban Areas Using a Presence and Background Learning Algorithm 期刊论文
REMOTE SENSING, 2017, 卷号: 9, 期号: 10
作者:  Ao, Zurui;  Su, Yanjun;  Li, Wenkai;  Guo, Qinghua;  Zhang, Jing
Adobe PDF(1859Kb)  |  收藏  |  浏览/下载：98/0  |  提交时间：2022/03/28
LiDAR  one-class classification  presence and background learning algorithm  remote sensing  
Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data 期刊论文
REMOTE SENSING OF ENVIRONMENT, 2016, 卷号: 173, 页码: 187-199
作者:  Su, Yanjun;  Guo, Qinghua;  Xue, Baolin;  Hu, Tianyu;  Alvarez, Otto;  Tao, Shengli;  Fang, Jingyun
Adobe PDF(4355Kb)  |  收藏  |  浏览/下载：88/0  |  提交时间：2022/07/08
Forest aboveground biomass  GIAS/ICESat  Lidar  Ground inventory  China  
A New Accuracy Assessment Method for One-Class Remote Sensing Classification 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 卷号: 52, 期号: 8, 页码: 4621-4632
作者:  Li, Wenkai;  Guo, Qinghua
Adobe PDF(2029Kb)  |  收藏  |  浏览/下载：32/0  |  提交时间：2023/03/30
Accuracy assessment  background  F-measure  negative  one-class remote sensing classification  positive  
How to assess the prediction accuracy of species presence-absence models without absence data? 期刊论文
ECOGRAPHY, 2013, 卷号: 36, 期号: 7, 页码: 788-799
作者:  Li, Wenkai;  Guo, Qinghua
Adobe PDF(1061Kb)  |  收藏  |  浏览/下载：32/0  |  提交时间：2023/04/25