We stand with Ukraine

We stand with Ukraine

Fei Zhu

Orcid: 0000-0002-8113-3707

Affiliations:

Tianjin University, Center for Applied Mathematics, China
University of Technology of Troyes, France

According to our database¹, Fei Zhu authored at least 20 papers between 2014 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

Online presence:

on orcid.org

On csauthors.net:

Bibliography

2024

Hyperspecral Unmixing Based on Multilinear Mixing Model Using Convolutional Autoencoders.

[BibT_eX]

[DOI]

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IEEE Trans. Geosci. Remote. Sens., 2024

2021

Improving deep hyperspectral image classification performance with spectral unmixing.

[BibT_eX]

[DOI]

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Signal Process., 2021

A kernel-based weight decorrelation for regularizing CNNs.

[BibT_eX]

[DOI]

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Neurocomputing, 2021

2020

Hyperspectral Image Classification With Deep Metric Learning and Conditional Random Field.

[BibT_eX]

[DOI]

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,

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IEEE Geosci. Remote. Sens. Lett., 2020

Boosting Deep Hyperspectral Image Classification with Spectral Unmixing.

[BibT_eX]

[DOI]

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CoRR, 2020

A Robust Multilinear Mixing Model with l2, 1 norm for Unmixing Hyperspectral Images.

[BibT_eX]

[DOI]

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,

Proceedings of the 2020 IEEE International Conference on Visual Communications and Image Processing, 2020

Pixel-Wise Linear/Nonlinear Nonnegative Matrix Factorization for Unmixing of Hyperspectral Data.

[BibT_eX]

[DOI]

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,

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

A CNN-Based Spatial Feature Fusion Algorithm for Hyperspectral Imagery Classification.

[BibT_eX]

[DOI]

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IEEE Trans. Geosci. Remote. Sens., 2019

Spectral-Spatial Feature Extraction and Classification by ANN Supervised With Center Loss in Hyperspectral Imagery.

[BibT_eX]

[DOI]

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IEEE Trans. Geosci. Remote. Sens., 2019

A Graph Regularized Multilinear Mixing Model for Nonlinear Hyperspectral Unmixing.

[BibT_eX]

[DOI]

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,

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Remote. Sens., 2019

2017

Correntropy Maximization via ADMM: Application to Robust Hyperspectral Unmixing.

[BibT_eX]

[DOI]

,

Abderrahim Halimi

,

,

,

IEEE Trans. Geosci. Remote. Sens., 2017

Online kernel nonnegative matrix factorization.

[BibT_eX]

[DOI]

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Signal Process., 2017

2016

Kernel nonnegative matrix factorization : application to hyperspectral imagery. (Factorisation en matrices non négatives à noyaux : application à l'imagerie hyperspectrale).

[BibT_eX]

[DOI]

PhD thesis, 2016

Biobjective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models.

[BibT_eX]

[DOI]

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IEEE Trans. Geosci. Remote. Sens., 2016

ADMM for maximum correntropy criterion.

[BibT_eX]

[DOI]

,

Abderrahim Halimi

,

,

,

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

Bi-Objective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models.

[BibT_eX]

[DOI]

,

CoRR, 2015

Online nonnegative matrix factorization based on kernel machines.

[BibT_eX]

[DOI]

,

Proceedings of the 23rd European Signal Processing Conference, 2015

Pareto front of bi-objective kernel-based nonnegative matrix factorization.

[BibT_eX]

[DOI]

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Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

Kernel nonnegative matrix factorization without the curse of the pre-image.

[BibT_eX]

[DOI]

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CoRR, 2014

Kernel nonnegative matrix factorization without the pre-image problem.

[BibT_eX]

[DOI]

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,

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

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