44 citations · 105 across the 8 of their papers we have counts for
8 papers
Nonlinear Hyperspectral Unmixing based on Multilinear Mixing Model using Convolutional Autoencoders
Tingting Fang, Fei Zhu, Jie Chen
Unsupervised spectral unmixing consists of representing each observed pixel as a combination of several pure materials called endmembers with their corresponding abundance fraction…
Improving Deep Hyperspectral Image Classification Performance with Spectral Unmixing
Alan J. X. Guo, Fei Zhu
Recent advances in neural networks have made great progress in the hyperspectral image (HSI) classification. However, the overfitting effect, which is mainly caused by complicated…
Hyperspectral Image Classification with Deep Metric Learning and Conditional Random Field
Yi Liang, Xin Zhao, Alan J. X. Guo +1
To improve the classification performance in the context of hyperspectral image processing, many works have been developed based on two common strategies, namely the spatial-spectr…
A CNN-based Spatial Feature Fusion Algorithm for Hyperspectral Imagery Classification
Alan J. X. Guo, Fei Zhu
The shortage of training samples remains one of the main obstacles in applying the artificial neural networks (ANN) to the hyperspectral images classification. To fuse the spatial…
Spectral-Spatial Feature Extraction and Classification by ANN Supervised with Center Loss in Hyperspectral Imagery
Alan J. X. Guo, Fei Zhu
In this paper, we propose a spectral-spatial feature extraction and classification framework based on artificial neuron network (ANN) in the context of hyperspectral imagery. With…
Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing
Fei Zhu, Abderrahim Halimi, Paul Honeine +2
In hyperspectral images, some spectral bands suffer from low signal-to-noise ratio due to noisy acquisition and atmospheric effects, thus requiring robust techniques for the unmixi…
Bi-Objective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models
Paul Honeine, Fei Zhu
Nonnegative matrix factorization (NMF) is a powerful class of feature extraction techniques that has been successfully applied in many fields, namely in signal and image processing…
Kernel Nonnegative Matrix Factorization Without the Curse of the Pre-image - Application to Unmixing Hyperspectral Images
Fei Zhu, Paul Honeine, Maya Kallas
The nonnegative matrix factorization (NMF) is widely used in signal and image processing, including bio-informatics, blind source separation and hyperspectral image analysis in rem…