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Ming Liu

4 papers here

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

author position
  • last author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.AR1
ORCID 0000-0002-1114-1728
same name
  • Ming Liu — 67 papers, h 87
  • Ming Liu — 57 papers, h 49
  • Ming Liu — 44 papers, h 12
  • Ming Liu — 29 papers, h 8
  • Ming Liu — 24 papers, h 9
  • Ming Liu — 24 papers, h 6

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

most citedCut-Thumbnail: A Novel Data Augmentation for Convolutional Neural Network

36 citations · 36 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AR2024

Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver

Hegan Chen, Jichang Yang, Jia Chen +20

Digital twins, the cornerstone of Industry 4.0, replicate real-world entities through computer models, revolutionising fields such as manufacturing management and industrial automa…

cs.CV2021

Feature Mining: A Novel Training Strategy for Convolutional Neural Network

Tianshu Xie, Xuan Cheng, Xiaomin Wang +3

In this paper, we propose a novel training strategy for convolutional neural network(CNN) named Feature Mining, that aims to strengthen the network's learning of the local feature.…

cs.CV2021

Go Small and Similar: A Simple Output Decay Brings Better Performance

Xuan Cheng, Tianshu Xie, Xiaomin Wang +3

Regularization and data augmentation methods have been widely used and become increasingly indispensable in deep learning training. Researchers who devote themselves to this have c…

cs.CV2021★ 36 cited

Cut-Thumbnail: A Novel Data Augmentation for Convolutional Neural Network

Tianshu Xie, Xuan Cheng, Minghui Liu +3

In this paper, we propose a novel data augmentation strategy named Cut-Thumbnail, that aims to improve the shape bias of the network. We reduce an image to a certain size and repla…

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