| Deep learning in remote sensing: A comprehensive review and list of resources XX Zhu, D Tuia, L Mou, GS Xia, L Zhang, F Xu, F Fraundorfer IEEE Geoscience and Remote Sensing Magazine 5 (4), 8-36, 2017 | 800 | 2017 |
| Tomographic SAR inversion by L1-norm regularization—The compressive sensing approach XX Zhu, R Bamler Geoscience and Remote Sensing, IEEE Transactions on 48 (10), 3839-3846, 2010 | 414 | 2010 |
| Very high resolution spaceborne SAR tomography in urban environment XX Zhu, R Bamler IEEE Transactions on Geoscience and Remote Sensing 48 (12), 4296-4308, 2010 | 370 | 2010 |
| Deep recurrent neural networks for hyperspectral image classification L Mou, P Ghamisi, XX Zhu IEEE Transactions on Geoscience and Remote Sensing 55 (7), 3639-3655, 2017 | 366 | 2017 |
| A sparse image fusion algorithm with application to pan-sharpening XX Zhu, R Bamler IEEE transactions on geoscience and remote sensing 51 (5), 2827-2836, 2012 | 306 | 2012 |
| Super-resolution power and robustness of compressive sensing for spectral estimation with application to spaceborne tomographic SAR XX Zhu, R Bamler IEEE Transactions on Geoscience and Remote Sensing 50 (1), 247-258, 2011 | 233 | 2011 |
| Demonstration of super-resolution for tomographic SAR imaging in urban environment XX Zhu, R Bamler IEEE Transactions on Geoscience and Remote Sensing 50 (8), 3150-3157, 2011 | 128 | 2011 |
| Learning spectral-spatial-temporal features via a recurrent convolutional neural network for change detection in multispectral imagery L Mou, L Bruzzone, XX Zhu IEEE Transactions on Geoscience and Remote Sensing 57 (2), 924-935, 2019 | 118 | 2019 |
| Unsupervised spectral–spatial feature learning via deep residual Conv–Deconv network for hyperspectral image classification L Mou, P Ghamisi, XX Zhu IEEE Transactions on Geoscience and Remote Sensing 56 (1), 391-406, 2017 | 117 | 2017 |
| An augmented linear mixing model to address spectral variability for hyperspectral unmixing D Hong, N Yokoya, J Chanussot, XX Zhu IEEE Transactions on Image Processing 28 (4), 1923-1938, 2018 | 116 | 2018 |
| Tomographic imaging and monitoring of buildings with very high resolution SAR data D Reale, G Fornaro, A Pauciullo, X Zhu, R Bamler IEEE Geoscience and remote sensing letters 8 (4), 661-665, 2011 | 106 | 2011 |
| Let's do the time warp: Multicomponent nonlinear motion estimation in differential SAR tomography XX Zhu, R Bamler IEEE Geoscience and Remote Sensing Letters 8 (4), 735-739, 2011 | 102 | 2011 |
| Data fusion and remote sensing: An ever-growing relationship M Schmitt, XX Zhu IEEE Geoscience and Remote Sensing Magazine 4 (4), 6-23, 2016 | 96 | 2016 |
| Interferometric potential of high resolution spaceborne SAR R Bamler, M Eineder, N Adam, X Zhu, S Gernhardt Photogrammetrie-Fernerkundung-Geoinformation 2009 (5), 407-419, 2009 | 91 | 2009 |
| Hyperspectral and LiDAR data fusion using extinction profiles and deep convolutional neural network P Ghamisi, B Höfle, XX Zhu IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2016 | 89 | 2016 |
| A self-improving convolution neural network for the classification of hyperspectral data P Ghamisi, Y Chen, XX Zhu IEEE Geoscience and Remote Sensing Letters 13 (10), 1537-1541, 2016 | 87 | 2016 |
| Extinction profiles for the classification of remote sensing data P Ghamisi, R Souza, JA Benediktsson, XX Zhu, L Rittner, RA Lotufo IEEE Transactions on Geoscience and Remote Sensing 54 (10), 5631-5645, 2016 | 87 | 2016 |
| Superresolving SAR tomography for multidimensional imaging of urban areas: Compressive sensing-based TomoSAR inversion XX Zhu, R Bamler IEEE Signal Processing Magazine 31 (4), 51-58, 2014 | 84 | 2014 |
| Building instance classification using street view images J Kang, M Körner, Y Wang, H Taubenböck, XX Zhu ISPRS journal of photogrammetry and remote sensing 145, 44-59, 2018 | 76 | 2018 |
| Facade reconstruction using multiview spaceborne TomoSAR point clouds XX Zhu, M Shahzad IEEE Transactions on Geoscience and Remote Sensing 52 (6), 3541-3552, 2013 | 69 | 2013 |
Richard BamlerGerman Aerospace Center (DLR) & Technical University of Munich確認したメール アドレス: dlr.de
