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  • 收录类型=EI x
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112 条 记 录,以下是 1-30

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Estimation of forest biomass dynamics in subtropical forests using multi-temporal airborne LiDAR data被引量:122收藏 分享
作者:Cao, Lin[1,2] Coops, Nicholas C.[2] Innes, John L.[2] Sheppard, Stephen R. J.[2] Fu, Liyong[3]
机构:Nanjing Forestry Univ;Univ British Columbia;Chinese Acad Forestry
来源:REMOTE SENSING OF ENVIRONMENT  2016
关键词:Multi-temporal   Airborne LiDAR   Subtropical forest   Biomass change   Forest growth   Canopy hEIght   Direct approach  
Nonpeaked Discriminant Analysis for Data Representation被引量:110收藏 分享
作者:Ye, Qiaolin[1,2] Li, Zechao[3] Fu, Liyong[2,4] Zhang, Zhao[5,6] Yang, Wankou[7]
机构:Nanjing Forestry Univ;Chinese Acad Forestry;Nanjing Univ Sci & Technol;Natl Forestry & Grassland Adm;Soochow Univ
来源:IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS  2019
关键词:Cutting L-norm distance   data classification   discriminant analysis   robustness  
Least squares twin bounded support vector machines based on L1-norm distance metric for classification被引量:85收藏 分享
作者:Yan, He[1] Ye, Qiaolin[1,4,5] Zhang, Tian'an[1,2] Yu, Dong-Jun[3] Yuan, Xia[3]
机构:Nanjing Forestry Univ;Nanjing Forestry Univ;Nanjing Univ Sci & Technol;Nanjing Univ Sci & Technol;Huaiyin Inst Technol
来源:PATTERN RECOGNITION  2018
关键词:L1-LSTBSVM   TBSVM   L1-norm distance   Outliers  
A generalized nonlinear mixed-effects hEIght to crown base model for Mongolian oak in northeast China被引量:76收藏 分享
作者:Fu, Liyong[1,2] Zhang, Huiru[1] Sharma, Ram P.[3] Pang, Lifeng[1] Wang, Guangxing[4]
机构:Chinese Acad Forestry;Penn State Univ;Czech Univ Life Sci Prague;Southern Illinois Univ Carbondale
来源:FOREST ECOLOGY AND MANAGEMENT  2017
关键词:Model calibration   Random effects   Heteroscedasticity   Two-level mixed-effects model   Optimal sample size  
Recurrent Thrifty Attention Network for Remote Sensing Scene Recognition被引量:73收藏 分享
作者:Fu, Liyong[1,2] Zhang, Dong[3] Ye, Qiaolin[4]
机构:Nanjing Forestry Univ;Chinese Acad Forestry;Nanjing Univ Sci & Technol;Nanjing Forestry Univ
来源:IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING  2021
关键词:Attention learning   convolutional neural networks (CNNs)   object detection   remote sensing scene (RSS) classification   RSS recognition  
RemoteCLIP: A Vision Language Foundation Model for Remote Sensing被引量:58收藏 分享
作者:Liu, Fan[1,2] Chen, Delong[3] Guan, Zhangqingyun[1] Zhou, Xiaocong[1] Zhu, Jiale[1]
机构:Hohai Univ;Minist Water Resources;Hong Kong Univ Sci & Technol;Nanjing Forestry Univ;Chinese Acad Forestry
来源:IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING  2024
关键词:Contrastive language image pretraining (CLIP)   foundation model   multimodality   remote sensing   vision-language  
Multiscale 3-D-2-D Mixed CNN and LightwEIght Attention-Free Transformer for Hyperspectral and LiDAR Classification被引量:57收藏 分享
作者:Sun, Le[1] Wang, Xinyu[2] Zheng, Yuhui[2,3] Wu, Zebin[2] Fu, Liyong[4]
机构:Nanjing Univ Informat Sci & Technol;Nanjing Univ Informat Sci & Technol;Qinghai Normal Univ;Chinese Acad Forestry
来源:IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING  2024
关键词:Convolutional neural network (CNN)   hyperspectral image (HSI)   joint classification   light detection and ranging (LiDAR) data   multiscale   transformer  
A generalized interregional nonlinear mixed-effects crown width model for Prince Rupprecht larch in northern China被引量:57收藏 分享
作者:Fu, Liyong[1,2] Sharma, Ram P.[3] Hao, Kaijie[4] Tang, Shouzheng[1]
机构:Chinese Acad Forestry;Penn State Univ;Czech Univ Life Sci;Shanxi Acad Forestry Sci
来源:FOREST ECOLOGY AND MANAGEMENT  2017
关键词:Crown width   Interregional effects   Optimal sample size   Random effects   Two-level mixed-effects model  
Compatible Biomass Model with Measurement Error Using Airborne LiDAR Data被引量:52收藏 分享
作者:Chen, Xingjing[1,2] Xie, Dongbo[1,2] Zhang, Zhuang[1,2] Sharma, Ram P.[3] Chen, Qiao[1,2]
机构:Chinese Acad Forestry;Natl Forestry & Grassland Adm;Tribhuwan Univ
来源:REMOTE SENSING  2023
关键词:airborne LiDAR   tree-components biomass   error-in-variable model   nonlinear seemingly unrelated regression  
Aboveground Biomass Prediction of Arid Shrub-Dominated Community Based on Airborne LiDAR through Parametric and Nonparametric Methods被引量:52收藏 分享
作者:Xie, Dongbo[1,2] Huang, Hongchao[1,2] Feng, Linyan[1,2] Sharma, Ram P.[3] Chen, Qiao[1]
机构:Chinese Acad Forestry;Natl Forestry & Grassland Adm;Tribhuwan Univeristy
来源:REMOTE SENSING  2023
关键词:aboveground biomass   LiDAR   shrub community   desert   nonparametric methods  
Robust capped L1-norm twin support vector machine被引量:51收藏 分享
作者:Wang, Chunyan[1,2] Ye, Qiaolin[1] Luo, Peng[2] Ye, Ning[1] Fu, Liyong[2]
机构:Nanjing Forestry Univ;Chinese Acad Forestry
来源:NEURAL NETWORKS  2019
关键词:Machine learning   TWSVM   Capped L1-norm   Robustness  
Lp- and Ls-Norm Distance Based Robust Linear Discriminant Analysis被引量:51收藏 分享
作者:Ye, Qiaolin[1,2] Fu, Liyong[1] Zhang, Zhao[3] Zhao, Henghao[2] Naiem, Meem[2]
机构:Chinese Acad Forestry;Nanjing Forestry Univ;Soochow Univ
来源:NEURAL NETWORKS  2018
关键词:linear Discriminant Analysis   Lp-norm   Ls-norm   Robustness  
CRNet: Channel-Enhanced Remodeling-Based Network for Salient Object Detection in Optical Remote Sensing Images被引量:49收藏 分享
作者:Sun, Le[1] Wang, Qing[2] Chen, Yuwen[4] Zheng, Yuhui[2,3] Wu, Zebin[2]
机构:Nanjing Univ Informat Sci & Technol;Nanjing Univ Informat Sci & Technol;Xidian Univ;Chinese Acad Sci;Chinese Acad Forestry
来源:IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING  2023
关键词:Channel enhance module (CEM)   optical remote sensing images (RSIS)   redefined feature module (RFM)   salient object detection (SOD)  
Comparison of seemingly unrelated regressions with error-in-variable models for developing a system of nonlinear additive biomass equations被引量:48收藏 分享
作者:Fu, Liyong[1] Lei, Yuancai[1] Wang, Guangxing[2,3] Bi, Huiquan[4] Tang, Shouzheng[1]
机构:Chinese Acad Forestry;Cent South Univ Forestry & Technol;So Illinois Univ;New South Wales Dept Ind & Investment;Xinyang Normal Univ
来源:TREES-STRUCTURE AND FUNCTION  2016
关键词:Additivity   Nonlinear error-in-variable models   Nonlinear seemingly unrelated regression   Tree biomass   Pinus massoniana Lamb  
A Hybrid Approach of Combining Random Forest with Texture Analysis and VDVI for Desert Vegetation Mapping Based on UAV RGB Data被引量:39收藏 分享
作者:Zhou, Huoyan[1,2] Fu, Liyong[2] Sharma, Ram P.[3] Lei, Yuancai[2] Guo, Jinping[1]
机构:Shanxi Agr Univ;Chinese Acad Forestry;Tribhuwan Univ
来源:REMOTE SENSING  2021
关键词:RF   Maximum likelihood classification   desertification  
Video Moment Retrieval With Noisy Labels被引量:37收藏 分享
作者:Pan, Wenwen[1] Zhao, Zhou[1] Huang, Wencan[1] Zhang, Zhu[1] Fu, Liyong[2,3]
机构:Zhejiang Univ;Chinese Acad Forestry;Natl Forestry & Grassland Adm;Hangzhou Dianzi Univ
来源:IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS  2024
关键词:Noise measurement   Annotations   Training   Manuals   Feature extraction   Deep learning   Task analysis   Co-teaching   feature pyramid network   multilevel losses   noisy label learning   video moment retrieval (VMR)  
BASNet: Burned Area Segmentation Network for Real-Time Detection of Damage Maps in Remote Sensing Images被引量:37收藏 分享
作者:Bo, Weihao[1] Liu, Jie[1] Fan, Xijian[1] Tjahjadi, Tardi[2] Ye, Qiaolin[1]
机构:Coll Informat Sci & Technol;Univ Warwick;Chinese Acad Forestry
来源:IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING  2022
关键词:Image segmentation   Semantics   Vegetation mapping   Optical imaging   Feature extraction   Autonomous aerial vehicles   Satellites   Burned area segmentation (BAS)   convolutional neural network (CNN)   forest fire monitoring   salient object detection (SOD)  
Performance and Sensitivity of Individual Tree Segmentation Methods for UAV-LiDAR in Multiple Forest Types被引量:36收藏 分享
作者:Ma, Kaisen[1,2,3] Chen, Zhenxiong[4] Fu, Liyong[1,5] Tian, Wanli[6] Jiang, Fugen[1,2,3]
机构:Cent South Univ Forestry & Technol;Key Lab Forestry Remote Sensing Based Big Data &;Key Lab State Forestry Adm Forest Resources Manag;Cent South Inventory & Planning Inst Natl Forestr;Chinese Acad Forestry
来源:REMOTE SENSING  2022
关键词:LiDAR   forest investigation   individual tree segmentation   tree detection   tree hEIght extraction  
Modelling a system of nonlinear additive crown width models applying seemingly unrelated regression for Prince Rupprecht larch in northern China被引量:35收藏 分享
作者:Fu, Liyong[1,2] Sharma, Ram P.[3] Wang, Guangxing[4] Tang, Shouzheng[1]
机构:Chinese Acad Forestry;Penn State Univ;Czech Univ Life Sci Prague;Southern Illinois Univ
来源:FOREST ECOLOGY AND MANAGEMENT  2017
关键词:Additivity   Dominant hEIght   Nonlinear seemingly unrelated regression   Adjustment in proportion   Ordinary least squares with separating regression  
Development of a System of Compatible Individual Tree Diameter and Aboveground Biomass Prediction Models Using Error-In-Variable Regression and Airborne LiDAR Data被引量:33收藏 分享
作者:Fu, Liyong[1] Liu, Qingwang[1] Sun, Hua[2,3] Wang, Qiuyan[1] Li, Zengyuan[1]
机构:Chinese Acad Forestry;Cent South Univ Forestry & Technol;Key Lab Forestry Remote Sensing Based Big Data &;Xinyang Normal Univ;Southern Illinois Univ
来源:REMOTE SENSING  2018
关键词:airborne LiDAR   diameter at breast hEIght   aboveground biomass   error-in-variable models   leave-one-out cross-validation  
A climate-sensitive aboveground biomass model for three larch species in northeastern and northern China被引量:31收藏 分享
作者:Fu, Liyong[1,2] Sun, Wei[3] Wang, Guangxing[4]
机构:Chinese Acad Forestry;Penn State Univ;Xinjiang Agr Univ;Southern Illinois Univ Carbondale
来源:TREES-STRUCTURE AND FUNCTION  2017
关键词:Larch species   Climate-sensitive aboveground biomass model   Nonlinear mixed-effects model   Dummy variable approach   Climate change  
Mapping the potential distribution suitability of 16 tree species under climate change in northeastern China using Maxent modelling被引量:27收藏 分享
作者:Liu, Dan[1] Lei, Xiangdong[1] Gao, Wenqiang[1] Guo, Hong[1] Xie, Yangsheng[1]
机构:Chinese Acad Forestry;Acad Forest Inventory & Planning Jilin Prov
来源:JOURNAL OF FORESTRY RESEARCH  0
关键词:Species distribution model   National forest inventory data   Natural forest   Climate change   Site suitability mapping   Maxent modelling  
Robust auto-wEIghted projective low-rank and sparse recovery for visual representation被引量:26收藏 分享
作者:Wang, Lei[1] Wang, Bangjun[1] Zhang, Zhao[1,2,3] Ye, Qiaolin[4] Fu, Liyong[5]
机构:Soochow Univ;Hefei Univ Technol;Hefei Univ Technol;Nanjing Forestry Univ;Chinese Acad Forestry
来源:NEURAL NETWORKS  2019
关键词:Auto-wEIghted low-rank and sparse recovery   Robust representation   Feature extraction   Classification  
Prediction of Individual Tree Diameter Using a Nonlinear Mixed-Effects Modeling Approach and Airborne LiDAR Data被引量:26收藏 分享
作者:Fu, Liyong[1,2,3] Duan, Guangshuang[2,4] Ye, Qiaolin[5] Meng, Xiang[2,3] Luo, Peng[2]
机构:Cent South Univ Forestry & Technol;Chinese Acad Forestry;Natl Forestry & Grassland Adm;Xinyang Normal Univ;Nanjing Forestry Univ
来源:REMOTE SENSING  2020
关键词:Picea crassifolia Kom   random effects   calibration   leave-one sub-sample plot-out cross- validation   prediction accuracy  
Preferred vector machine for forest fire detection被引量:26收藏 分享
作者:Yang, Xubing[1] Hua, Zhichun[1] Zhang, Li[1] Fan, Xijian[1] Zhang, Fuquan[1]
机构:Nanjing Forestry Univ;Nanjing Forestry Univ;Chinese Acad Forestry
来源:PATTERN RECOGNITION  2023
关键词:Forest fire detection   Fire detection rate   Error warning rate   SVM   Dual representation  
Additivity of nonlinear tree crown width models: Aggregated and disaggregated model structures using nonlinear simultaneous equations被引量:24收藏 分享
作者:Lei, Yakai[1,2] Fu, Liyong[3] Affleck, David L. R.[4] Nelson, Andrew S.[5] Shen, Chenchen[5]
机构:Nanjing Audit Univ;Henan Agr Univ;Chinese Acad Forestry;Univ Montana;Univ Idaho
来源:FOREST ECOLOGY AND MANAGEMENT  2018
关键词:Crown width   Additivity property   Nonlinear simultaneous equations   Nonlinear seemingly unrelated regression   Adjustment in proportion   Ordinary least squares with separating regression  
Pixel-level automatic annotation for forest fire image被引量:24收藏 分享
作者:Yang, Xubing[1] Chen, Run[1] Zhang, Fuquan[1] Zhang, Li[1,2] Fan, Xijian[1]
机构:Nanjing Forestry Univ;Nanjing Univ Aeronaut & Astronaut;Chinese Acad Forestry
来源:ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE  2021
关键词:Fire detection   Convex hull   Pixel-level   Image annotation  
Estimating crown width in degraded forest: A two-level nonlinear mixed-effects crown width model for Dacrydium pierrEI and Podocarpus imbricatus in tropical China被引量:23收藏 分享
作者:Chen, Qiao[1,5] Duan, Guangshuang[2] Liu, Qingwang[1,4] Ye, Qiaolin[3] Sharma, Ram P.[4]
机构:Chinese Acad Forestry;Xinyang Normal Univ;Nanjing Forestry Univ;Tribhuwan Univ;NFGA
来源:FOREST ECOLOGY AND MANAGEMENT  2021
关键词:Dummy variable modeling   Empirical best linear unbiased prediction   Heteroscedasticity   Random effects   Response calibration   Variance function  
Robust discriminant feature selection via joint L-2,L-1-norm distance minimization and maximization被引量:22收藏 分享
作者:Yang, Zhangjing[1] Ye, Qiaolin[2,3] Chen, Qiao[4,5] Ma, Xu[2] Fu, Liyong[4,5]
机构:Nanjing Audit Univ;Nanjing Forestry Univ;Huaiyin Inst Technol;Chinese Acad Forestry;Natl Forestry & Grassland Adm
来源:KNOWLEDGE-BASED SYSTEMS  2020
关键词:Feature selection   L-2,L-1-norm   Discriminative Feature Selection   Robustness  
Nonlinear mixed-effects hEIght to crown base model based on both airborne LiDAR and field datasets for Picea crassifolia Kom trees in northwest China被引量:21收藏 分享
作者:Yang, Zhaohui[1,3] Liu, Qingwang[1] Luo, Peng[1] Ye, Qiaolin[2] Sharma, Ram P.[4]
机构:Chinese Acad Forestry;Nanjing Forestry Univ;Natl Forestry & Grassland Adm;Tribhuwan Univ
来源:FOREST ECOLOGY AND MANAGEMENT  2020
关键词:Random effects   Heteroscedasticity   EBLUP   Subject-specific prediction   Calibration  
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