Stefan Oehmcke
Assistant Professor
- 2023
- Published
Multi-scale pseudo labeling for unsupervised deep edge detection
Zhou, C., Yuan, C., Wang, H., Li, Lei, Oehmcke, Stefan, Liu, J. & Peng, J., 2023, In: Knowledge-Based Systems. 280, 15 p., 111057.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Predicting urban tree cover from incomplete point labels and limited background information
Zhang, Hui, Kariryaa, Ankit, Guthula, Venkanna Babu, Igel, Christian & Oehmcke, Stefan, 2023, Urban-AI 2023 - Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI. Omitaomu, O. A., Mostafavi, A. & Liu, Y. (eds.). Association for Computing Machinery, Inc., p. 52-60Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Remember to Correct the Bias When Using Deep Learning for Regression!
Igel, Christian & Oehmcke, Stefan, 2023, In: KI - Kunstliche Intelligenz. 37, 1, p. 33-40Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Satellite-based continental-scale inventory of European wetland types at 10m spatial resolution
Kovács, Gyula Mate, Oehmcke, Stefan, Horion, Stéphanie, Gominski, Dimitri Pierre Johannes, Tong, Xiaoye & Fensholt, Rasmus, 2023. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
- Published
Seasonal-Trend Time Series Decomposition on Graphics Processing Units
Serykh, Dmitry, Oehmcke, Stefan, Oancea, Cosmin Eugen, Masiliunas, D., Verbesselt, J., Cheng, Yan, Horion, Stéphanie, Gieseke, F. & Hinnerskov, Nikolaj Hey, 2023, Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. He, J., Palpanas, T., Hu, X., Cuzzocrea, A., Dou, D., Slezak, D., Wang, W., Gruca, A., Lin, J. C-W. & Agrawal, R. (eds.). IEEE, p. 5914-5923 10 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2024
- Published
Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR
Oehmcke, Stefan, Li, Lei, Trepekli, Aikaterini, Caballer Revenga, Jaime, Nord-Larsen, Thomas, Gieseke, Fabian Cristian & Igel, Christian, 2024, In: Remote Sensing of Environment. 302, 21 p., 113968.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Scattered tree death contributes to substantial forest loss in California
Cheng, Yan, Oehmcke, Stefan, Brandt, Martin Stefan, Rosenthal, L., Das, A., Vrieling, A., Saatchi, S., Wagner, F., Mugabowindekwe, Maurice, Verbruggen, Wim, Beier, Claus & Horion, Stéphanie, 2024, In: Nature Communications. 15, 1, p. 1-13 641.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
High-resolution mapping of tree mortality in European forests
Cheng, Yan, Oehmcke, Stefan, Mosig, C., Beloiu, M., Kattenborn, T., Abel, Christin, Gominski, Dimitri Pierre Johannes, Nord-Larsen, Thomas, Fensholt, Rasmus & Horion, Stéphanie, 11 Mar 2024.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
ID: 209373892
Most downloads
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119
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Creating cloud-free satellite imagery from image time series with deep learning
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published -
105
downloads
Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
69
downloads
Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
Research output: Contribution to journal › Journal article › Research › peer-review
Published