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Hao Lu 0004
Person information
- affiliation: Beijing Forestry University, School of Information Science and Technology, Beijing, China
Other persons with the same name
- Hao Lu — disambiguation page
- Hao Lu 0001 — Washington State University, Pullman, WA, USA
- Hao Lu 0002 — Beijing Institute of Technology, School of Computer Science and Technology, Beijing, China
- Hao Lu 0003 — University of Adelaide, Australia (and 1 more)
- Hao Lu 0005 — Shandong Normal University, College of Physics and Electronics Science, Jinan, China
- Hao Lu 0006 — University of Notre Dame, Department of Electrical Engineering, Notre Dame, IN, USA
- Hao Lu 0007 — Army Engineering University of PLA, Nanjing, China
- Hao Lu 0008 — University of Science and Technology of China, Wireless Information Network Laboratory, Department of Electronic Engineering and Information Science, Hefei, China
- Hao Lu 0009 — Hong Kong University of Science and Technology, Hong Kong (and 1 more)
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2020 – today
- 2024
- [j9]Jun Chen, Han Wang, Hao Lu:
Aircraft Detection in SAR Images via Point Features. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - 2023
- [j8]Yisha Wang, Gang Yang, Hao Lu:
A Domain-Adaptive Tree-Crown Detection and Counting Method Based on Cascade Region Proposal Networks. Algorithms 16(7): 309 (2023) - 2022
- [j7]Bowen Li, Hao Lu, Han Wang, Jianbo Qi, Gang Yang, Yong Pang, Haolin Dong, Yining Lian:
Terrain-Net: A Highly-Efficient, Parameter-Free, and Easy-to-Use Deep Neural Network for Ground Filtering of UAV LiDAR Data in Forested Environments. Remote. Sens. 14(22): 5798 (2022) - 2021
- [j6]Yining Lian, Zhongke Feng, Yongjian Huai, Hao Lu, Shilin Chen, Niwen Li:
Terrestrial Videogrammetry for Deriving Key Forest Inventory Data: A Case Study in Plantation. Remote. Sens. 13(16): 3138 (2021) - 2020
- [j5]Zhenyu Ma, Yong Pang, Di Wang, Xiaojun Liang, Bowei Chen, Hao Lu, Holger Weinacker, Barbara Koch:
Individual Tree Crown Segmentation of a Larch Plantation Using Airborne Laser Scanning Data Based on Region Growing and Canopy Morphology Features. Remote. Sens. 12(7): 1078 (2020)
2010 – 2019
- 2019
- [j4]Bowei Chen, Yong Pang, Zengyuan Li, Hao Lu, Luxia Liu, Peter R. J. North, Jacqueline Rosette:
Ground and Top of Canopy Extraction From Photon-Counting LiDAR Data Using Local Outlier Factor With Ellipse Searching Area. IEEE Geosci. Remote. Sens. Lett. 16(9): 1447-1451 (2019) - [j3]Bowei Chen, Yong Pang, Zengyuan Li, Peter R. J. North, Jacqueline Rosette, Guoqing Sun, Juan Suárez, Iain Bye, Hao Lu:
Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest. Remote. Sens. 11(7): 856 (2019) - 2018
- [c4]Bowei Chen, Yong Pang, Zengyuan Li, Peter R. J. North, Jacqueline A. B. Rosette, I. J. Bye, Hao Lu, Liuxia Liu, Zhenyu Ma:
Simulation and Signal Detection of Photon Counting Lidar Data in Forested Area. IGARSS 2018: 3547-3550 - 2016
- [j2]Yong Pang, Zengyuan Li, Hongbo Ju, Hao Lu, Wen Jia, Lin Si, Ying Guo, Qingwang Liu, Shiming Li, Luxia Liu, Binbin Xie, Bingxiang Tan, Yuanyong Dian:
LiCHy: The CAF's LiDAR, CCD and Hyperspectral Integrated Airborne Observation System. Remote. Sens. 8(5): 398 (2016) - [c3]Yong Pang, Zengyuan Li, Wen Jia, Hao Lu, Bowei Chen, Yongjie Xia, Guang Zheng, Xianlian Gao, Qiang Wang:
An airborne multi-angle hyperspectral experiment in a boreal forest of Northeast China. IGARSS 2016: 1217-1220 - [c2]Yong Pang, Zengyuan Li, Shili Meng, Hao Lu, Wen Jia, Qingwang Liu, Haikui Li, Yuancai Lei:
China typical forest aboveground biomass estimation by fusion of multi-platform data. IGARSS 2016: 3557-3560 - 2015
- [j1]Hao Lu, Yong Pang, Zengyuan Li, Bowei Chen:
An Automatic Range Ambiguity Solution in High-Repetition-Rate Airborne Laser Scanner Using Priori Terrain Prediction. IEEE Geosci. Remote. Sens. Lett. 12(11): 2232-2236 (2015) - [c1]Hao Lu, Yong Pang:
A waveform exploitation optimized multiscale curvature algorithm for recognizing ground echoes from airborne laser scanner in densely forested area. Geoinformatics 2015: 1-5
Coauthor Index
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last updated on 2024-12-26 00:49 CET by the dblp team
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