170 citations · 357 across the 9 of their papers we have counts for
17 papers
EOD: The IEEE GRSS Earth Observation Database
Michael Schmitt, Pedram Ghamisi, Naoto Yokoya +1
In the era of deep learning, annotated datasets have become a crucial asset to the remote sensing community. In the last decade, a plethora of different datasets was published, eac…
SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud Removal
Patrick Ebel, Yajin Xu, Michael Schmitt +1
About half of all optical observations collected via spaceborne satellites are affected by haze or clouds. Consequently, cloud coverage affects the remote sensing practitioner's ca…
There is no data like more data -- current status of machine learning datasets in remote sensing
Michael Schmitt, Seyed Ali Ahmadi, Ronny Hänsch
Annotated datasets have become one of the most crucial preconditions for the development and evaluation of machine learning-based methods designed for the automated interpretation…
Remote Sensing Image Classification with the SEN12MS Dataset
Michael Schmitt, Yu-Lun Wu
Image classification is one of the main drivers of the rapid developments in deep learning with convolutional neural networks for computer vision. So is the analogous task of scene…
Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster Data
Gerald Baier, Antonin Deschemps, Michael Schmitt +1
We synthesize both optical RGB and synthetic aperture radar (SAR) remote sensing images from land cover maps and auxiliary raster data using generative adversarial networks (GANs).…
Mapping horizontal and vertical urban densification in Denmark with Landsat time-series from 1985 to 2018: a semantic segmentation solution
Tzu-Hsin Karen Chen, Chunping Qiu, Michael Schmitt +3
Landsat imagery is an unparalleled freely available data source that allows reconstructing horizontal and vertical urban form. This paper addresses the challenge of using Landsat d…