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Jie Zhu

4 papers here

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.RO1
  • math.NA1
ORCID 0000-0003-0330-6382
same name
  • Jie Zhu — 13 papers, h 8
  • Jie Zhu — 12 papers, h 3
  • Jie Zhu — 11 papers, h 4
  • Jie Zhu — 8 papers, h 31
  • Jie Zhu — 8 papers, h 4
  • Jie Zhu — 7 papers, h 20

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

most citedLearning to Rank Onset-Occurring-Offset Representations for Micro-Expression Recognition

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

math.NA2023

Low rank approximation method for perturbed linear systems with applications to elliptic type stochastic PDEs

Yujun Zhu, Ju Ming, Jie Zhu +1

In this paper, we propose a low rank approximation method for efficiently solving stochastic partial differential equations. Specifically, our method utilizes a novel low rank appr…

cs.CV2023★ 2 cited

Learning to Rank Onset-Occurring-Offset Representations for Micro-Expression Recognition

Jie Zhu, Yuan Zong, Jingang Shi +3

This paper focuses on the research of micro-expression recognition (MER) and proposes a flexible and reliable deep learning method called learning to rank onset-occurring-offset re…

cs.RO2023

Fairness-Sensitive Policy-Gradient Reinforcement Learning for Reducing Bias in Robotic Assistance

Jie Zhu, Mengsha Hu, Xueyao Liang +3

Robots assist humans in various activities, from daily living public service (e.g., airports and restaurants), and to collaborative manufacturing. However, it is risky to assume th…

cs.CV2021

MSP : Refine Boundary Segmentation via Multiscale Superpixel

Jie Zhu, Huabin Huang, Banghuai Li +2

In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. Inspired by the generated sharp edges…

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