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Xiao Xiang Zhu
Researcher at German Aerospace Center
Publications - 572
Citations - 18577
Xiao Xiang Zhu is an academic researcher from German Aerospace Center. The author has contributed to research in topics: Computer science & Synthetic aperture radar. The author has an hindex of 51, co-authored 484 publications receiving 11002 citations. Previous affiliations of Xiao Xiang Zhu include Technische Universität München & Wageningen University and Research Centre.
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Journal ArticleDOI
Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources
Xiao Xiang Zhu,Devis Tuia,Lichao Mou,Gui-Song Xia,Liangpei Zhang,Feng Xu,Friedrich Fraundorfer +6 more
TL;DR: The challenges of using deep learning for remote-sensing data analysis are analyzed, recent advances are reviewed, and resources are provided that hope will make deep learning in remote sensing seem ridiculously simple.
Journal ArticleDOI
Deep learning in remote sensing: a review
Xiao Xiang Zhu,Devis Tuia,Lichao Mou,Gui-Song Xia,Liangpei Zhang,Feng Xu,Friedrich Fraundorfer +6 more
TL;DR: In this article, the authors analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with.
Journal ArticleDOI
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing
TL;DR: This work proposes a novel spectral mixture model, called the augmented LMM, to address spectral variability by applying a data-driven learning strategy in inverse problems of hyperspectral unmixing and introduces a spectral variability dictionary.
Journal ArticleDOI
Tomographic SAR Inversion by $L_{1}$ -Norm Regularization—The Compressive Sensing Approach
Xiao Xiang Zhu,Richard Bamler +1 more
TL;DR: In this article, compressive sensing (CS) methods for tomographic reconstruction of a building complex from the TerraSAR-X spotlight data are presented, and the theory of 4-D (differential, i.e., space-time) CS TomoSAR and compares it with parametric (nonlinear least squares) and nonparametric (singular value decomposition) reconstruction methods.
Journal ArticleDOI
Very High Resolution Spaceborne SAR Tomography in Urban Environment
Xiao Xiang Zhu,Richard Bamler +1 more
TL;DR: First 3-D and 4-D reconstructions of an entire building complex with very high level of detail from spaceborne SAR data by pixelwise TomoSAR are presented.