仅罗列中科院一区和IF>10期刊:
1. Zhou J.H., Yun, T* (2026). Knowledge Distillation enhanced Lightweight Pruned Graph Neural Network for Urban Scenario Sensing using Consumer-Grade LiDAR Devices, IEEE Transactions on Consumer Electronics. 2026 (指导硕士生)
2. Jiang K, Yun, T* (2026). Spherical-Harmonic Deep Learning Framework for GenericTree Morphology and Species Identification. ISPRS Journal of Photogrammetry and Remote Sensing. (指导研究生), 欧洲大数据集双盲竞赛2026年分类精度最高,参赛名yunwengjiang. https://www.codabench.org/competitions/3667/#/results-tab
3. Liu, Z., Yun, T*. (2026). A multi-phase phenological framework for reducing spectral confusion in disturbed forests: A case study from Vietnam. Journal of Cleaner Production 544, 147694 (指导硕士生)
4. Yun, T., et al. (2025). LGINet: Linguistic guided image diffusion model for tree species generation and identification from aerial imagery. Information Fusion, 103912
5. Yun, T., et al. (2025). A framework for phenotyping rubber trees under intense wind stress using laser scanning and digital twin technology. Agricultural and Forest Meteorology, 361, 110319
6. Yun, T., et al. (2024). Status, advancements and prospects of deep learning methods appliedin forest studies. International Journal of Applied Earth Observation and Geoinformation, 131,103938.
7. X Wang, B Chen, T Yun*. (2024). Early identification of immature rubber plantations using Landsat and Sentinel satellite images. International Journal of Applied Earth Observation and Geoinformation. 133, 104097. (指导硕士生).
8. Y Gao, T Yun, B Chen*. (2024). Improving the accuracy of canopy height mapping in rubber plantations based on stand age, multi-source satellite images, and random forest algorithm. International Journal of Applied Earth Observation and Geoinformation, 1-17. (指导硕士生).
9. Yun, T., Jiang, K., et al. (2021). Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization-based approach [J]. Remote Sensing of Environment, 2021, 256: 112307.
10. Yun, T., Cao, L., An, F., et al. Simulation of multi-platform LiDAR for assessing total leaf area in tree crowns [J]. Agricultural and Forest Meteorology, 2019, 276: 107610.
11. Xue X.B., Yun, T.*. Shortwave radiation calculation for forest plots using airborne LiDAR data and computer graphics, Plant phenomics. Volume 2022.(指导硕士生).
12. 张宇,云挺,等. 基于计算机模拟模型的林木冠层太阳短波辐射定量分析方法 [J]. 林业科学, 2024, 60 (04): 16-30.
近五年授权的部分知识产权:
1. 云挺等,天地空一体化森林碳汇监测技术规程,T/CCPEF 080—2024,团体标准,中国林业与环境促进会,团体标准。2024.
2. 云挺, (1/3). A method of Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization.PCT international application. Submission number:364931, application number: CN2020/119150. PCT专利美国授权
3. 云挺, (1/6).Leaf surface reconstruction and physically based deformation simulation based on the point cloud data. Patent number: 2020103131, Innovation patent of Australian. 澳大利亚发明
4. 云挺,(1/4)。基于深度学习的番茄病虫害检测与识别方法[P], 授权公告日2025.9, 专利号:ZL202310606757.4,授权公告号:CN116630803B。(发明专利)
5. 云挺,(1/4)。基于优化模糊深度网络的林木胸径材积精准预测方法[P], 授权公告日2025.9, 专利号:ZL202211316076.6,授权公告号:CN115546179B。(发明专利)
4. 云挺,(1/4)。基于端到端深度学习方法的单株树冠检测方法[P], 授权公告日2024.9, 授权公告号CN112907520B。(发明专利)
5. 云挺,(1/4)。基于深度学习与机载激光点云的单株树冠分割方法[P], 授权公告日2024.9, 授权公告号CN112819830B。(发明专利)
6. 云挺,(1/4)。基于深度学习与机载激光点云的单株树冠分割方法[P], 授权公告日2024.9, 授权公告号CN112819830B。(发明专利)
7. 云挺,(1/4)。基于多孔介质理论和计算机图形学的树冠孔隙率估算方法[P], 授权公告日2025.5, 专利号:ZL202111352735.7,授权公告号:CN114066966 B。(发明专利)
8. 云挺,(1/4)。基于计算机模拟模型的林木冠层太阳短波辐射定量分析方法[P],授权公告日2025.4, 授权公告号CN116306123B。(发明专利)
9. 云挺,(1/4)。基于点云数据和计算机图形学的林分辐射通量计算方法[P], 授权公告日2024.3, 授权公告号CN114663786B。(发明专利)
10. 云挺,(1/4)。晶格投影的深度学习网络阔叶树枝叶分离与骨架重建方法[P], 授权公告日2024.3, 授权公告号CN114494586B。(发明专利)
11. 云挺,(1/4)。基于超像素与拓扑特征的航拍图像单株树冠分割算法[P], 授权公告日2024.3, 授权公告号CN111340826B。(发明专利)
12. 云挺,(1/4)。面向机载激光点云的倒水蔓延与能量函数控制的单株树冠分割方法[P], 授权公告日2024.3, 授权公告号CN110598707B。(发明专利)
13. 云挺,(1/4). 基于Faster R-CNN的面向激光点云的单木分割方法[P]. 申请日 2019.6, 专利号ZL201910551190.9, 授权公告日2023.6, 授权公告号CN110378909B。(发明专利)
14. 云挺,(1/4). 一种基于激光点云的活立木叶属性精准估测方法[P]. 申请日 2019.2, 专利号ZL201910130528.3, 授权公告日2023.4, 授权公告号CN109961470B。(发明专利)
15. 云挺,(1/5). 基于激光点云与空气动力学的活立木抗风性能分析方法[P]. 申请日 2018.11, 专利号ZL201811322277.0, 授权公告日2022.12, 授权公告号CN109446691B。(发明专利)
16. 云挺,(1/4).一种面向树木激光点云的有效特征抽取与树种识别方法.申请日 2018.10,专利号ZL201811263570.4, 授权公告日2021.9,授权公告号CN109446986B。(发明专利)
17. 云挺,(1/4).一种基于激光雷达点云数据的树种分类方法.申请日 2018.10,专利号ZL201811263568.7,授权公告日2021.8,授权公告号CN109409429B。(发明专利)
18. 云挺,(1/4). 激光点云中林木参数评估方法[P].申请日 2017.10,专利号ZL201710955957.5, 授权公告日2020.10,授权公告号CN107705309B。(发明专利)
19. 云挺,(1/3). 一种基于激光点云数据的真实阔叶树器官分类识别方法[P].申请日 2014.8, 专利号ZL201410436294.2, 授权公告日2019.4, 授权公告号CN105373814B。(发明专利)
20. 云挺,(2/3). 面向激光点云数据的阔叶树真实叶片建模与形变方法[P]. 申请日 2014.9, 专利号ZL201410436293.8,批准年份2019.1, 授权公告号CN105654543B。(发明专利)
21. 云挺,(1/3). 基于激光扫描数据的树木冠层叶面积计算方法[P]. 申请日 2016.5, 专利号ZL201610350345.9, 授权公告日2018.8, 授权公告号CN105806266B。(发明专利)
22. 云挺,(1/3).一种基于级联循环网络的林木生长参数预测方法[P]. 申请日 2023.4, 专利号ZL202310448728.X, 授权公告日2026.2,授权公告号:CN 117011694B。(发明专利)
23. 云挺,(1/3). 基于深度学习方法的林木激光点云枝叶分离方法. 申请日:2021.9,专利号:ZL 202111137023.3, 授权公告日2026.3, 授权公告号:CN 115880487B。(发明专利)