Peer reviewed journal papers
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(2024): Transformer Models for Land Cover Classification with Satellite Image Time Series. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, Vol. 92, 547-568.
DOI: 10.1007/s41064-024-00299-7 -
(2021): Classification and Change Detection in Mobile Mapping LiDAR Point Clouds, PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science
DOI: 10.1007/s41064-021-00148-x
Peer reviewed conference papers
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(2023): Transformer models for multi-temporal land cover classification using remote sensing images. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023, pp. 981–990.
DOI: 10.5194/isprs-annals-X-1-W1-2023-981-2023 -
(2022): Investigating 2D and 3D convolutions for multitemporal land cover classification using remote sensing images. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022, pp. 271–279.
DOI: 10.5194/isprs-annals-V-3-2022-271-2022 -
(2022): Deep learning for the detection of early signs for forest damage based on satellite imagery. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2022, pp. 307–315.
DOI: 10.5194/isprs-annals-V-2-2022-307-2022 -
(2021): Investigations on feature similarity and the impact of training data for land cover classification. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2021, pp. 181–189.
DOI: https://doi.org/10.5194/isprs-annals-V-3-2021-181-2021
Non-reviewed conference papers
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(2020): Automatically generated training data for land cover classification with CNNs using Sentinel-2 images. In: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 767–774.
DOI: 10.5194/isprs-archives-XLIII-B3-2020-767-2020