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L. Zhan

12 papers hereh-index 293k citations132 works total

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

author position
  • middle author8
  • last author4

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.CV4
  • q-bio.NC2
  • eess.IV1
same name
  • L. Zhan — 12 papers, h 26
  • L. Zhan — 8 papers, h 22
  • L. Zhan — 5 papers, h 31
  • L. Zhan — 3 papers, h 2
  • L. Zhan — 2 papers, h 2
  • L. Zhan — 1 paper, h 33

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
20172023
most citedAdversarial Attack on Hierarchical Graph Pooling Neural Networks

22 citations · 43 across the 11 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2021★ 4 cited

PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images

Haozhe Jia, Haoteng Tang, Guixiang Ma +4

Automated and accurate segmentation of the infected regions in computed tomography (CT) images is critical for the prediction of the pathological stage and treatment response of CO…

cs.CV2021

Boundary-aware Graph Reasoning for Semantic Segmentation

Haoteng Tang, Haozhe Jia, Weidong Cai +3

In this paper, we propose a Boundary-aware Graph Reasoning (BGR) module to learn long-range contextual features for semantic segmentation. Rather than directly construct the graph…

cs.CV2021★ 5 cited

Multiplex Graph Networks for Multimodal Brain Network Analysis

Zhaoming Kong, Lichao Sun, Hao Peng +3

In this paper, we propose MGNet, a simple and effective multiplex graph convolutional network (GCN) model for multimodal brain network analysis. The proposed method integrates tens…

cs.CV2020★ 1 cited

Deep Representation Learning For Multimodal Brain Networks

Wen Zhang, Liang Zhan, Paul Thompson +1

Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology…

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