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Xiaodan Liang

119 papers hereh-index 7723.2k citations182 works total

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

author position
  • first author17
  • middle author87
  • last author10

Across the 114 of 119 papers where every author was matched, so the position is known.

fields
  • cs.CV93
  • cs.LG12
  • cs.CL9
  • q-bio.QM3
  • cs.AI1
  • cs.RO1
same name
  • Xiaodan Liang — 47 papers, h 27
  • Xiaodan Liang — 47 papers, h 34
  • Xiaodan Liang — 25 papers, h 8
  • Xiaodan Liang — 23 papers, h 8
  • Xiaodan Liang — 18 papers, h 5
  • Xiaodan Liang — 16 papers, h 10

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
20142023
most citedSTC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation

619 citations · 3.7k across the 114 of their papers we have counts for

collaborators
Showing q-bio.QMShow all

3 papers · 1 filter

q-bio.QM2018★ 6 cited

Image-derived generative modeling of pseudo-macromolecular structures - towards the statistical assessment of Electron CryoTomography template matching

Kai Wen Wang, Xiangrui Zeng, Xiaodan Liang +3

Cellular Electron CryoTomography (CECT) is a 3D imaging technique that captures information about the structure and spatial organization of macromolecular complexes within single c…

q-bio.QM2018★ 1 cited

Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms

Chang Liu, Xiangrui Zeng, Ruogu Lin +4

Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique for the 3D visualization of cellular structure and organization at submolecular resolution. It enables anal…

q-bio.QM2017★ 49 cited

Deep learning based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms

Min Xu, Xiaoqi Chai, Hariank Muthakana +4

Motivation: Cellular Electron CryoTomography (CECT) enables 3D visualization of cellular organization at near-native state and in sub-molecular resolution, making it a powerful too…

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