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Ling Zhang

Alibaba DAMO Academy USA

12 papers hereh-index 212.3k citations27 works total

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

author position
  • first author7
  • middle author2
  • last author3

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

fields
  • cs.CV9
  • eess.IV3
affiliations
  • Alibaba DAMO Academy USA
same name
  • Ling Zhang — 24 papers, h 14
  • Ling Zhang — 11 papers, h 58
  • Ling Zhang — 10 papers, h 2
  • Ling Zhang — 9 papers, h 12
  • Ling Zhang — 8 papers, h 5
  • Ling Zhang — 7 papers, h 4

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
20172020
most citedDeepPap: Deep Convolutional Networks for Cervical Cell Classification

423 citations · 591 across the 12 of their papers we have counts for

collaborators
Showing 2020Show all

3 papers · 1 filter

eess.IV2020

3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management

Tianyi Zhao, Kai Cao, Jiawen Yao +6

The pancreatic disease taxonomy includes ten types of masses (tumors or cysts)[20,8]. Previous work focuses on developing segmentation or classification methods only for certain ma…

eess.IV2020

DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Contrast-Enhanced CT Imaging

Jiawen Yao, Yu Shi, Le Lu +2

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and carries a dismal prognosis. Surgery remains the best chance of a potential cure for patients who are e…

eess.IV2020★ 5 cited

Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans

Ling Zhang, Yu Shi, Jiawen Yao +5

Accurate and automated tumor segmentation is highly desired since it has the great potential to increase the efficiency and reproducibility of computing more complete tumor measure…

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