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researcher

Peng Liu

96 papers hereh-index 8038.1k citations2.2k works total

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

author position
  • first author23
  • middle author48
  • last author19

Across the 90 of 96 papers where every author was matched, so the position is known.

fields
  • cs.LG15
  • eess.IV10
  • gr-qc10
  • cs.CR9
  • cs.CV9
  • hep-th8
same name
  • Peng Liu — 32 papers, h 77
  • Peng Liu — 31 papers, h 17
  • Peng Liu — 19 papers, h 9
  • Peng Liu — 12 papers, h 4
  • Peng Liu — 11 papers, h 4
  • Peng Liu — 10 papers, h 5

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
20112026
most citedObservation of plaid-like spin splitting in a noncoplanar antiferromagnet

254 citations · 1.1k across the 96 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

eess.IV2019★ 1 cited

KRNET: Image Denoising with Kernel Regulation Network

Peng Liu, Xiaoxiao Zhou, Junyiyang Li +2

One popular strategy for image denoising is to design a generalized regularization term that is capable of exploring the implicit prior underlying data observation. Convolutional n…

eess.IV2019

SDCNet: Smoothed Dense-Convolution Network for Restoring Low-Dose Cerebral CT Perfusion

Peng Liu, Ruogu Fang

With substantial public concerns on potential cancer risks and health hazards caused by the accumulated radiation exposure in medical imaging, reducing radiation dose in X-ray base…

eess.IV2019

CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation

Peng Liu, Bin Kong, Zhongyu Li +2

Recently, deep neural networks have demonstrated comparable and even better performance with board-certified ophthalmologists in well-annotated datasets. However, the diversity of…

cs.CV2019★ 2 cited

Image Restoration Using Deep Regulated Convolutional Networks

Peng Liu, Xiaoxiao Zhou, Yangjunyi Li +2

While the depth of convolutional neural networks has attracted substantial attention in the deep learning research, the width of these networks has recently received greater intere…

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