Jingzhi Tu
Orcid: 0000-0001-8292-9582
According to our database1,
Jingzhi Tu
authored at least 10 papers
between 2020 and 2023.
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Bibliography
2023
A Deep Learning Approach for Long-Term Traffic Flow Prediction With Multifactor Fusion Using Spatiotemporal Graph Convolutional Network.
IEEE Trans. Intell. Transp. Syst., August, 2023
Physics-Informed Neural Network Integrating PointNet-Based Adaptive Refinement for Investigating Crack Propagation in Industrial Applications.
IEEE Trans. Ind. Informatics, 2023
2022
SWCGAN: Generative Adversarial Network Combining Swin Transformer and CNN for Remote Sensing Image Super-Resolution.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
An improved Nyström spectral graph clustering using <i>k</i>-core decomposition as a sampling strategy for large networks.
J. King Saud Univ. Comput. Inf. Sci., 2022
An Efficient Deep Learning Approach Using Improved Generative Adversarial Networks for Incomplete Information Completion of Self-driving Vehicles.
J. Grid Comput., 2022
2021
An Efficient Deep Learning Approach Using Improved Generative Adversarial Networks for Incomplete Information Completion of Self-driving.
CoRR, 2021
An efficient graph clustering algorithm by exploiting <i>k</i>-core decomposition and motifs.
Comput. Electr. Eng., 2021
2020
Comparative investigation of parallel spatial interpolation algorithms for building large-scale digital elevation models.
PeerJ Comput. Sci., 2020
Comput. Sci. Rev., 2020
KCoreMotif: An Efficient Graph Clustering Algorithm for Large Networks by Exploiting k-core Decomposition and Motifs.
CoRR, 2020