Michael Schmitt

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	All	Since 2016
Citations	1132	956
h-index	21	19
i10-index	37	30

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Co-authors

Xiao Xiang ZhuProfessor for Data Science in Earth Observation, TUM & Department Head "EO Data Science", DLRVerified email at tum.de
Uwe StillaTechnische Universitaet MuenchenVerified email at tum.de
Lloyd HughesTechnical University of MunichVerified email at tum.de
Lichao MouGerman Aerospace Center (DLR), Technical University of Munich (TUM)Verified email at dlr.de
Stefan AuerRemote Sensing Technology Institute, German Aerospace Center (DLR)Verified email at dlr.de
Yuanyuan WangDepartment of EO Data Science, German Aerospace CenterVerified email at tum.de
Pedram GhamisiHelmholtz-Zentrum Dresden-Rossendorf, Division Exploration, Machine Learning Group (head)Verified email at hzdr.de
Johannes L. SchönbergerSenior Scientist, MicrosoftVerified email at microsoft.com
Christophe MagnardSenior scientist, Gamma Remote Sensing AGVerified email at gamma-rs.ch
Muhammad ShahzadSchool of Electrical Engineering & Computer Science (SEECS), National University of SciencesVerified email at seecs.edu.pk
Dorota IwaszczukTechnische Universität DarmstadtVerified email at tu-darmstadt.de
Ludwig HoegnerAkademischer Rat, Technische Universitaet MuenchenVerified email at tum.de
Yilei ShiChair of Remote Sensing Technology, Technical University of MunichVerified email at tum.de
Peter ReinartzHead of Department at German Aerospace Center (DLR), Prof. at University of OsnabrueckVerified email at dlr.de
Qingyu LiTechnical university of MunichVerified email at tum.de
Patrick EbelTechnical University of MunichVerified email at tum.de
Yuansheng HuaSignal Processing in Earth Observation, Technical University of Munich (TUM) & Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR)Verified email at dlr.de
Tzu-Hsin Karen ChenPhD fellow, Aarhus UniversityVerified email at envs.au.dk
Claas GrohnfeldtPrincipal Research Engineer @ Huawei TechnologiesVerified email at huawei.com
Marco KörnerTechnische Universität MünchenVerified email at tum.de

Michael Schmitt

Munich University of Applied Sciences

Verified email at hm.edu - Homepage

Geospatial Data Science Data Fusion Remote Sensing Machine Learning Synthetic Aperture Radar


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Data fusion and remote sensing - an ever-growing relationship M Schmitt, XX Zhu IEEE Geoscience and Remote Sensing Magazine 4 (4), 6-23, 2016	103	2016
Identifying corresponding patches in SAR and optical images with a pseudo-siamese CNN LH Hughes, M Schmitt, L Mou, Y Wang, XX Zhu IEEE Geoscience and Remote Sensing Letters 15 (5), 784-788, 2018	57	2018
The SEN1-2 dataset for deep learning in SAR-optical data fusion M Schmitt, LH Hughes, XX Zhu ISPRS Technical Commission I Symposium, 2018	47	2018
Maximum-likelihood-based approach for single-pass synthetic aperture radar tomography over urban areas M Schmitt, U Stilla IET Radar, Sonar & Navigation 8 (9), 1145-1153, 2014	41	2014
Compressive Sensing Based Layover Separation in Airborne Single-Pass Multi-Baseline InSAR Data M Schmitt, U Stilla IEEE Geoscience and Remote Sensing Letters 10 (2), 313-317, 2013	39	2013
Adaptive Multilooking of Airborne Single-Pass Multi-baseline InSAR Stacks M Schmitt, U Stilla IEEE Transactions on Geoscience and Remote Sensing 52 (1), 305-312, 2014	36	2014
SEN12MS - A curated dataset of georeferenced multi-spectral Sentinel-1/2 imagery for deep learning and data fusion M Schmitt, LH Hughes, C Qiu, XX Zhu ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2019	31	2019
Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network C Qiu, L Mou, M Schmitt, XX Zhu ISPRS Journal of Photogrammetry and Remote Sensing 154, 151-162, 2019	30	2019
Analysing changes of the Poyang Lake water area using Sentinel-1 synthetic aperture radar imagery L Zeng, M Schmitt, L Li, XX Zhu International Journal of Remote Sensing 38 (23), 7041-7069, 2017	30	2017
A CNN for the Identification of Corresponding Patches in SAR and Optical Imagery of Urban Scenes L Mou, M Schmitt, Y Wang, X Zhu 2017 Joint Urban Remote Sensing Event, 2017	29	2017
Adaptive covariance matrix estimation for multi-baseline InSAR data stacks M Schmitt, JL Schönberger, U Stilla IEEE Transactions on Geoscience and Remote Sensing 52 (11), 6807-6817, 2014	29	2014
Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas M Schmitt, U Stilla ISPRS Journal of Photogrammetry and Remote Sensing 87, 68-77, 2014	28	2014
A Conditional Generative Adversarial Network to Fuse Sar And Multispectral Optical Data For Cloud Removal From Sentinel-2 Images C Grohnfeldt, M Schmitt, X Zhu IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018	27	2018
Feature importance analysis for local climate zone classification using a residual convolutional neural network with multi-source datasets C Qiu, M Schmitt, L Mou, P Ghamisi, XX Zhu Remote Sensing 10 (10), 1572, 2018	27	2018
Fusion of SAR and optical remote sensing data - challenges and recent trends M Schmitt, F Tupin, XX Zhu IEEE Geoscience and Remote Sensing Symposium (IGARSS 2017), 5458-5461, 2017	23	2017
Reconstruction of individual trees from multi-aspect TomoSAR data M Schmitt, M Shahzad, XX Zhu Remote Sensing of Environment 165, 175-185, 2015	23	2015
So2Sat LCZ42: A benchmark dataset for global local climate zones classification XX Zhu, J Hu, C Qiu, Y Shi, J Kang, L Mou, H Bagheri, M Häberle, Y Hua, ... arXiv preprint arXiv:1912.12171, 2019	22*	2019
Mining hard negative samples for SAR-optical image matching using generative adversarial networks LH Hughes, M Schmitt, XX Zhu Remote Sensing 10 (10), 1552, 2018	22	2018
SAR-to-Optical Image Translation Based on Conditional Generative Adversarial Networks—Optimization, Opportunities and Limits M Fuentes Reyes, S Auer, N Merkle, C Henry, M Schmitt Remote Sensing 11 (17), 2067, 2019	21	2019
Object-Based Multipass InSAR via Robust Low-Rank Tensor Decomposition J Kang, Y Wang, M Schmitt, XX Zhu IEEE Transactions on Geoscience and Remote Sensing 56 (6), 3062-3077, 2018	21	2018

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