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Real-Time and Accurate Segmentation of 3-D Point Clouds Based on Gaussian Process Regression

  • Published:2017-12 Issue:12 Volume:18 Page:3363-3377
  • ISSN:1524-9050
  • Container-title:IEEE Transactions on Intelligent Transportation Systems
  • language:
  • Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Shin Myung-OkORCID,Oh Gyu-Min,Kim Seong-WooORCID,Seo Seung-Woo

Funder

National Research Foundation of Korea Grant Funded by the Ministry of Science, ICT and Future Planning

Institute of New Media and Communications and the Automation and Systems Research Institute, Seoul National University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Cited by 36 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Drivable Region Completion via a 3D LiDAR;IEEE Transactions on Intelligent Transportation Systems;2024-08

2. Point Cloud Clustering Segmentation Algorithm for Indoor and Outdoor Environments;Proceedings of the 2024 4th International Conference on Robotics and Control Engineering;2024-06-27

3. Domain Adaptive LiDAR Point Cloud Segmentation via Density-Aware Self-Training;IEEE Transactions on Intelligent Transportation Systems;2024

4. A machine learning approach to analyzing spatiotemporal impacts of mobility restriction policies on infection rates;Transportation Research Part A: Policy and Practice;2023-10

5. GaPro: Box-Supervised 3D Point Cloud Instance Segmentation Using Gaussian Processes as Pseudo Labelers;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01
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