79 citations · 161 across the 8 of their papers we have counts for
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cs.CV2023★ 1 cited
AE-RED: A Hyperspectral Unmixing Framework Powered by Deep Autoencoder and Regularization by Denoising
Min Zhao, Jie Chen, Nicolas Dobigeon
Spectral unmixing has been extensively studied with a variety of methods and used in many applications. Recently, data-driven techniques with deep learning methods have obtained gr…
cs.CV2020★ 1 cited
Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors
Min Zhao, Tiande Gao, Jie Chen +1
Nowadays, nonnegative matrix factorization (NMF) based methods have been widely applied to blind spectral unmixing. Introducing proper regularizers to NMF is crucial for mathematic…
cs.CV2019★ 1 cited
A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation
Min Zhao, Jie Chen, Zhe He
Spectral unmixing is an important and challenging problem in hyperspectral data processing. This topic has been extensively studied and a variety of unmixing algorithms have been p…