Weiming Hu

Orcid: 0000-0001-9483-5559

Affiliations:
  • Southeast University, Nanjing, Jiangsu, China


According to our database1, Weiming Hu authored at least 12 papers between 2019 and 2025.

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

Timeline

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Bibliography

2025
VDI-Net: Viewpoint Changes and Dynamic Interference Immune Place Recognition Network for Intelligent Vehicles Based on Multiview Images.
IEEE Internet Things J., September, 2025

2024
TopSPR-Net: Topology Aware Segment-Level Point Cloud Learning Descriptors for Three-Dimensional Place Recognition in Large-Scale Environments.
IEEE Trans. Ind. Electron., October, 2024

A Cooperative Control Methodology Considering Dynamic Interaction for Multiple Connected and Automated Vehicles in the Merging Zone.
IEEE Trans. Intell. Transp. Syst., September, 2024

Robust 3D Semantic Segmentation Method Based on Multi-Modal Collaborative Learning.
Remote. Sens., February, 2024

Circuit Implementation Enabling Full-Scale Linear Sensing in Mode-Localized Sensors.
IEEE Trans. Instrum. Meas., 2024

An Enhanced-LiDAR/UWB/INS Integrated Positioning Methodology for Unmanned Ground Vehicle in Sparse Environments.
IEEE Trans. Ind. Informatics, 2024

Illumination Robust Semantic Segmentation Based on Cross-Dimensional Multispectral Edge Fusion in Dynamic Traffic Scenes.
IEEE Access, 2024

2023
Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors.
Sensors, November, 2023

Explicit Points-of-Interest Driven Siamese Transformer for 3D LiDAR Place Recognition in Outdoor Challenging Environments.
IEEE Trans. Ind. Informatics, October, 2023

Learning a Novel LiDAR Submap-Based Observation Model for Global Positioning in Long-Term Changing Environments.
IEEE Trans. Ind. Electron., 2023

2022
A Roadside Decision-Making Methodology Based on Deep Reinforcement Learning to Simultaneously Improve the Safety and Efficiency of Merging Zone.
IEEE Trans. Intell. Transp. Syst., 2022

2019
A Novel Heading Angle Estimation Methodology for Land Vehicles Based on Deep Learning and Enhanced Digital Map.
IEEE Access, 2019


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