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Haiyang Wu
Observed name:
H. Wu
Institutions:
International Institute for Geo-Information Science and Earth Observation,
University of Twente
Observed institutions:
International Institute for Geo-Information Science and Earth Observation,
University of Twente,
Capital Normal University
ORCID:
0000-0003-2560-8509
Observed ORCIDs:
0000-0003-2560-8509,
0000-0003-0157-9926
OpenAlex ID:
A5011545767
Planar Constraint Assisted LiDAR SLAM Algorithm Based on Manhattan World Assumption
2022
·
Haiyang Wu
, Wei Wu
, et al.
·
Remote Sensing
·
12
PDF
Mercator Descriptor: A Novel Global Descriptor for Loop Closure Detection in LiDAR SLAM
2024
·
Zhibo Wang
, Donghai Xie
, et al.
·
IEEE Sensors Journal
·
7
Remote Sensing Image Intelligent Interpretation From a Language-Centered Perspective: Principles, methods, and challenges
2026
·
Haifeng Li
, Wang Guo
, et al.
·
IEEE Geoscience and Remote Sensing Magazine
·
4
PDF
Gaussian or Plane? Both: Semantic-Driven Voxel Representation for LiDAR–Inertial Odometry
2025
·
Haiyang Wu
, George Vosselman
, et al.
·
IEEE Robotics and Automation Letters
·
3
PDF
An Indoor Laser Inertial SLAM Method Fusing Semantics and Planes
2025
·
Chaohong Wu
, Ruofei Zhong
, et al.
·
The Photogrammetric Record
·
2
RAVEN++: Pinpointing Fine-Grained Violations in Advertisement Videos with Active Reinforcement Reasoning
2025
·
Deyi Ji
, Yuekui Yang
, et al.
·
Conference on Empirical Methods in Natural Language Processing (EMNLP)
·
2
PDF
Feasibility of Indoor Frame-Wise Lidar Semantic Segmentation via Distillation from Visual Foundation Model
2026
·
Haiyang Wu
, Juan J. Gonzales Torres
, et al.
·
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
·
1
Mr-md:multi-robot Mapping With Manhattan Descriptor
2023
·
H. Wu
, R. Zhong
, et al.
·
The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
PDF
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Works count:
8
Citation count:
31
H-index:
3
I10-index:
1
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