Xingzhu Liang
Orcid: 0000-0002-8674-7302
According to our database1,
Xingzhu Liang
authored at least 28 papers
between 2013 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Multi-granularity enhanced feature learning for visible-infrared person re-identification.
J. Supercomput., January, 2025
Federated split learning via dynamic aggregation and homomorphic encryption on non-IID data.
J. Supercomput., January, 2025
2024
Multim. Syst., October, 2024
EDFIDepth: enriched multi-path vision transformer feature interaction networks for monocular depth estimation.
J. Supercomput., September, 2024
Mach. Vis. Appl., September, 2024
Expert Syst. J. Knowl. Eng., September, 2024
J. Supercomput., July, 2024
J. Supercomput., May, 2024
J. Real Time Image Process., April, 2024
RCFNet: Related cross-level feature network with cascaded self-distillation for monocular depth estimation.
Digit. Signal Process., 2024
2023
Vis. Comput., December, 2023
J. Intell. Fuzzy Syst., December, 2023
Appl. Intell., May, 2023
SiamLight: lightweight networks for object tracking via attention mechanisms and pixel-level cross-correlation.
J. Real Time Image Process., April, 2023
Coupled locality discriminant analysis with globality preserving for dimensionality reduction.
Appl. Intell., March, 2023
IEEE Trans. Consumer Electron., 2023
Parameter-free marginal fisher analysis based on L<sub>2,1</sub>-norm regularisation for face recognition.
Int. J. Comput. Sci. Eng., 2023
2022
2021
PeerJ Comput. Sci., 2021
IEEE Access, 2021
2020
Int. J. Comput. Sci. Eng., 2020
2018
Enhanced Parameter-Free Diversity Discriminant Preserving Projections for Face Recognition.
Int. J. Pattern Recognit. Artif. Intell., 2018
2016
Maximal Margin Local Preserving Median Fisher Discriminant Analysis for Face Recognition.
J. Softw., 2016
Proceedings of the 3rd International Conference on Systems and Informatics, 2016
2013
Kernel semi-supervised marginal fisher analysis and its application to face recognition.
Proceedings of the Ninth International Conference on Natural Computation, 2013
Kernel Optimal Unsupervised Discriminant Projection and Its Application to Face Recognition.
Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications, 2013