Wen Zeng

Orcid: 0000-0002-1550-7926

Affiliations:
  • China University of Geosciences, Wuhan, Hubei, China


According to our database1, Wen Zeng authored at least 11 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
Hierarchical structure-based model for importance and reliability assessment of water distribution networks.
Reliab. Eng. Syst. Saf., 2025

Risk assessment of water distribution networks through an integrated model based on machine learning and statistical methods.
Reliab. Eng. Syst. Saf., 2025

2024
A parallel framework on hybrid architectures for raster-based geospatial cellular automata models.
Int. J. Geogr. Inf. Sci., July, 2024

2023
MDC-Net: a multi-directional constrained and prior assisted neural network for wood and leaf separation from terrestrial laser scanning.
Int. J. Digit. Earth, December, 2023

mcRPL: a general purpose parallel raster processing library on distributed heterogeneous architectures.
Int. J. Geogr. Inf. Sci., September, 2023

2022
S<sup>3</sup>TRM: Spectral-Spatial Unmixing of Hyperspectral Imagery Based on Sparse Topic Relaxation-Clustering Model.
IEEE Trans. Geosci. Remote. Sens., 2022

cuFSDAF: An Enhanced Flexible Spatiotemporal Data Fusion Algorithm Parallelized Using Graphics Processing Units.
IEEE Trans. Geosci. Remote. Sens., 2022

2021
Variability in and mixtures among residential vacancies at granular levels: Evidence from municipal water consumption data.
Comput. Environ. Urban Syst., 2021

A Sparse Topic Relaxion and Group Clustering Model for Hyperspectral Unmixing.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

A Union Framework with Sparse Topic Relaxion and Group Clustering for Hyperspectral Unmixing.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Semi-Automatic Fully Sparse Semantic Modeling Framework for Hyperspectral Unmixing.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020


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