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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-1
https://doi.org/10.5194/isprs-archives-XLII-1-19-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLII-1-19-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
26 Sep 2018
| 26 Sep 2018
SEGMENT-AND-COUNT: VEHICLE COUNTING IN AERIAL IMAGERY USING ATROUS CONVOLUTIONAL NEURAL NETWORKS
S. Azimi
German Aerospace Center (DLR), Remote Sensing Technology Institute, D-82234 Weßling, Germany
E. Vig
German Aerospace Center (DLR), Remote Sensing Technology Institute, D-82234 Weßling, Germany
F. Kurz
German Aerospace Center (DLR), Remote Sensing Technology Institute, D-82234 Weßling, Germany
P. Reinartz
German Aerospace Center (DLR), Remote Sensing Technology Institute, D-82234 Weßling, Germany
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Short summary
Short summary
Multimodal data fusion is an intuitive strategy to break the limitation of individual data in Earth observation. Here, we present a multimodal data set, named MDAS, consisting of synthetic aperture radar (SAR), multispectral, hyperspectral, digital surface model (DSM), and geographic information system (GIS) data for the city of Augsburg, Germany, along with baseline models for resolution enhancement, spectral unmixing, and land cover classification, three typical remote sensing applications.
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