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researcher

Meilin Liu

School of Materials Science and Engineering , Georgia Institute of Technology , Atlanta , Georgia 30332-0245 , United States.

21 papers hereh-index 10746.2k citations905 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author7
  • last author13

Across the 20 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.RO3
  • cond-mat.mtrl-sci2
  • cs.DC2
  • cs.ET2
  • math.OC1
affiliations
  • School of Materials Science and Engineering , Georgia Institute of Technology , Atlanta , Georgia 30332-0245 , United States.
Homepage
same name
  • Meilin Liu — 3 papers, h 1
  • Meilin Liu — 2 papers, h 2
  • Meilin Liu — 1 paper, h 8
  • Meilin Liu — 1 paper, h 3
  • Meilin Liu — 1 paper, h 5
  • Meilin Liu — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132023
most citedRNGDet: Road Network Graph Detection by Transformer in Aerial Images

79 citations · 208 across the 21 of their papers we have counts for

collaborators
Showing cs.ROShow all

3 papers · 1 filter

cs.RO2022★ 2 cited

Monocular Camera Mapping with Pose-Guided Optimization: Enhancing Marking-Level HD Map Accuracy

Hongji Liu, Linwei Zheng, Xiaoyang Yan +4

Marking-level high-definition maps (HD maps) are of great significance for autonomous vehicles (AVs), especially in large-scale, appearance-changing scenarios where AVs rely on mar…

cs.RO2022★ 20 cited

Real-time Neural Dense Elevation Mapping for Urban Terrain with Uncertainty Estimations

Bowen Yang, Qingwen Zhang, Ruoyu Geng +2

Having good knowledge of terrain information is essential for improving the performance of various downstream tasks on complex terrains, especially for the locomotion and navigatio…

cs.RO2022★ 1 cited

Real-Time Trajectory Planning for Autonomous Driving with Gaussian Process and Incremental Refinement

Cheng Jie, Chen Yingbing, Zhang Qingwen +2

Real-time kinodynamic trajectory planning in dynamic environments is critical yet challenging for autonomous driving. In this letter, we propose an efficient trajectory planning sy…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.