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David Zhang

4 papers hereh-index 201.9k citations36 works total

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

author position
  • last author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • David Zhang — 11 papers
  • David Zhang — 5 papers, h 25
  • David Zhang — 3 papers, h 7
  • David Zhang — 2 papers, h 33
  • David Zhang — 2 papers
  • David Zhang — 1 paper, h 38

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
20182021
most citedDS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentation

43 citations · 46 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2021★ 43 cited

DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentation

Ailiang Lin, Bingzhi Chen, Jiayu Xu +2

Automatic medical image segmentation has made great progress benefit from the development of deep learning. However, most existing methods are based on convolutional neural network…

cs.CV2021

Dual-Stream Reciprocal Disentanglement Learning for Domain Adaptation Person Re-Identification

Huafeng Li, Kaixiong Xu, Jinxing Li +4

Since human-labeled samples are free for the target set, unsupervised person re-identification (Re-ID) has attracted much attention in recent years, by additionally exploiting the…

cs.CV2019★ 1 cited

Manifold Criterion Guided Transfer Learning via Intermediate Domain Generation

Lei Zhang, Shanshan Wang, Guang-Bin Huang +3

In many practical transfer learning scenarios, the feature distribution is different across the source and target domains (i.e. non-i.i.d.). Maximum mean discrepancy (MMD), as a do…

cs.CV2018★ 2 cited

Dual Asymmetric Deep Hashing Learning

Jinxing Li, Bob Zhang, Guangming Lu +1

Due to the impressive learning power, deep learning has achieved a remarkable performance in supervised hash function learning. In this paper, we propose a novel asymmetric supervi…

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