成果/Result

Leaf image based plant disease identification using transfer learning and feature fusion被引量：81收藏 分享

作者：Fan, Xijian[1] Luo, Peng[2,3] Mu, Yuen[1] Zhou, Rui[1] Tjahjadi, Tardi[4]

机构：Nanjing Forestry Univ;Chinese Acad Forestry;Natl Forestry & Grassland Adm;Univ Warwick;Natl Forestry & Grassland Adm

来源：COMPUTERS AND ELECTRONICS IN AGRICULTURE  2022

关键词：Plant disease   Transfer learning   Feature fusion   Convolutional neural network  

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  

Optimizing kNN for Mapping Vegetation Cover of Arid and Semi-Arid Areas Using Landsat Images被引量：33收藏 分享

作者：Sun, Hua[1,2,3] Wang, Qing[4] Wang, Guangxing[1,2,3,4] Lin, Hui[1,2,3] Luo, Peng[5]

机构：Cent South Univ Forestry & Technol;Key Lab Forestry Remote Sensing Based Big Data &;Key Lab State Forestry Adm Forest Resources Manag;Southern Illinois Univ;Chinese Acad Forestry

来源：REMOTE SENSING  2018

关键词：land degradation   optimized k-nearest nEIghbors   landsat image   percentage vegetation cover   Duolun County   Kangbao County  

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  

From Laboratory to Field: Unsupervised Domain Adaptation for Plant Disease Recognition in the Wild被引量：25收藏 分享

作者：Wu, Xinlu[1] Fan, Xijian[1] Luo, Peng[2,3] Das Choudhury, Sruti[4] Tjahjadi, Tardi[5]

机构：Nanjing Forestry Univ;Chinese Acad Forestry;Natl Forestry & Grassland Adm;Univ Nebraska;Univ Warwick

来源：PLANT PHENOMICS  2023

关键词：Learning systems  

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  

Prediction of Individual Tree Diameter and HEIght to Crown Base Using Nonlinear Simultaneous Regression and Airborne LiDAR Data被引量：16收藏 分享

作者：Yang, Zhaohui[1,2] Liu, Qingwang[1] Luo, Peng[1] Ye, Qiaolin[3] Duan, Guangshuang[1,4]

机构：Chinese Acad Forestry;Natl Forestry & Grassland Adm;Nanjing Forestry Univ;Xinyang Normal Univ;Tribhuwan Univ

来源：REMOTE SENSING  2020

关键词：Picea crassifoliaKom   compatible equation   nonlinear seemingly unrelated regression   error-in-variable modeling   leave-one-out cross-validation  

Multi-view generalized support vector machine via mining the inherent relationship between views with applications to face and fire smoke recognition被引量：16收藏 分享

作者：Cheng, Yawen[1,2] Fu, Liyong[3] Luo, Peng[3] Ye, Qiaolin[1,2] Liu, Fan[4]

机构：Nanjing Forestry Univ;Huaiyin Inst Technol;Chinese Acad Forestry;Hohai Univ

来源：KNOWLEDGE-BASED SYSTEMS  2020

关键词：Multi-view learning   GEPSVM   Co-regularization  

Developing a spectral angle based vegetation index for detecting the early dying process of Chinese fir trees被引量：13收藏 分享

作者：Zang, Zhuo[1,2,3] Wang, Guangxing[3] Lin, Hui[1,2] Luo, Peng[4]

机构：Cent South Univ Forestry & Technol;Key Lab Forestry Remote Sensing Based Big Data &;Southern Illinois Univ Carbondale;Chinese Acad Forestry

来源：ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING  2021

关键词：Hyperspectral data   Spectral angle   GRRSGI   Early stage damage detection   Chinese fir  

Analysis of the Spatial Differences in Canopy HEIght Models from UAV LiDAR and Photogrammetry被引量：12收藏 分享

作者：Liu, Qingwang[1,2] Fu, Liyong[1,3] Chen, Qiao[1] Wang, Guangxing[4] Luo, Peng[1]

机构：Chinese Acad Forestry;Natl Forestry & Grassland Adm;Natl Forestry & Grassland Adm;Southern Illinois Univ;Tribhuwan Univ

来源：REMOTE SENSING  2020

关键词：digital surface model   digital terrain model   canopy hEIght model   constrained nEIghbor interpolation   ordinary nEIghbor interpolation   point cloud density   stereo imagery