Nannan Qin

Orcid: 0000-0003-0641-6122

According to our database1, Nannan Qin authored at least 11 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
RdmkNet & Toronto-RDMK: Large-Scale Datasets for Road Marking Classification and Segmentation.
IEEE Trans. Intell. Transp. Syst., October, 2024

A Survey of Point Cloud Completion.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

A feature perturbation weakly supervised learning network for airborne multispectral LiDAR pointcloud classification.
Int. J. Appl. Earth Obs. Geoinformation, 2024

Weakly Supervised Point Cloud Segmentation by Combining Active Learning Annotation and Multi-Consistency Mechanism.
Proceedings of the IGARSS 2024, 2024

Multi-Granularity Feature Fusion For Point Cloud Semantic Segmentation Under Urban Scenes.
Proceedings of the IGARSS 2024, 2024

2023
Towards intelligent ground filtering of large-scale topographic point clouds: A comprehensive survey.
Int. J. Appl. Earth Obs. Geoinformation, December, 2023

Deep Ground Filtering of Large-Scale ALS Point Clouds via Iterative Sequential Ground Prediction.
Remote. Sens., February, 2023

2021
Semantic Segmentation of UAV Lidar Point Clouds of a Stack Interchange with Deep Neural Networks.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

OpenGF: An Ultra-Large-Scale Ground Filtering Dataset Built Upon Open ALS Point Clouds Around the World.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Semantic Labeling of ALS Point Cloud via Learning Voxel and Pixel Representations.
IEEE Geosci. Remote. Sens. Lett., 2020

Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020


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