activity
20182023
most citedStressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction

145 citations · 166 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023

IC classifier: a classifier for 3D industrial components based on geometric prior using GNN

Zipeng Lin, Zhenguo Nie

In this paper, we propose an approach to address the problem of classifying 3D industrial components by introducing a novel framework named IC-classifier (Industrial Component clas…

cs.CE2021★ 1 cited

SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Metal Forming Stress Field with Attention Mechanism and Perceptual Features

Qingfeng Xu, Zhenguo Nie, Handing Xu +2

In stress field analysis, the finite element analysis is a crucial approach, in which the mesh-density has a significant impact on the results. High mesh density usually contribute…

math.NA2021

SuperMeshing: A Novel Method for Boosting the Mesh Density in Numerical Computation within 2D Domain

Handing Xu, Zhenguo Nie, Qingfeng Xu +1

Due to the limit of mesh density, the improvement of the spatial precision of numerical computation always leads to a decrease in computing efficiency. Aiming at this inability of…

cs.LG2021

Artificial Intelligence Enhanced Rapid and Efficient Diagnosis of Mycoplasma Pneumoniae Pneumonia in Children Patients

Chenglin Pan, Kuan Yan, Xiao Liu +5

Artificial intelligence methods have been increasingly turning into a potentially powerful tool in the diagnosis and management of diseases. In this study, we utilized logistic reg…

cs.CV2020★ 145 cited

StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction

Haoliang Jiang, Zhenguo Nie, Roselyn Yeo +2

Using deep learning to analyze mechanical stress distributions has been gaining interest with the demand for fast stress analysis methods. Deep learning approaches have achieved ex…

cs.CE2020★ 15 cited

TopologyGAN: Topology Optimization Using Generative Adversarial Networks Based on Physical Fields Over the Initial Domain

Zhenguo Nie, Tong Lin, Haoliang Jiang +1

In topology optimization using deep learning, load and boundary conditions represented as vectors or sparse matrices often miss the opportunity to encode a rich view of the design…

hep-ph2018★ 5 cited

The TauSpinner approach for electroweak corrections in LHC Z to ll observables

E. Richter-Was, Z. Was

The LHC enters era of the Standard Model Z-boson couplings precise measurements, to match precision of LEP. The calculations of electroweak (EW) corrections in the Monte Carlo gene…