Stefan Oehmcke
Assistant Professor
ORCID: 0000-0002-0240-1559
1 - 5 out of 5Page size: 10
- 2021
- Published
Attentional feature fusion
Dai, Y., Gieseke, Fabian Cristian, Oehmcke, Stefan, Wu, Y. & Barnard, K., 2021, Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021. IEEE, p. 3559-3568Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Both sides of the story: comparing student-level data on reading performance from administrative registers to application generated data from a reading app
Sortkær, B., Smith, E., Reimer, D., Oehmcke, Stefan & Andersen, I. G., 2021, In: EPJ Data Science. 10, 1, 21 p., 44.Research output: Contribution to journal › Journal article › peer-review
- Published
Estimating Forest Canopy Height with Multi-Spectral and Multi-Temporal Imagery Using Deep Learning
Oehmcke, Stefan, Nyegaard-Signori, T., Grogan, K. & Gieseke, Fabian Cristian, 2021, Proceedings - 2021 IEEE International Conference on Big Data, Big Data 2021. Chen, Y., Ludwig, H., Tu, Y., Fayyad, U., Zhu, X., Hu, X. T., Byna, S., Liu, X., Zhang, J., Pan, S., Papalexakis, V., Wang, J., Cuzzocrea, A. & Ordonez, C. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 4915-4924 10 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Plant Structure and Carbon Storage Assessment Utilizing Drone-Borne Lidar and Deep Learning Technologies in a Danish Agricultural Expanse.
Trepekli, Aikaterini, Revenga, J. C., Oehmcke, Stefan, Gieseke, Fabian Cristian, Jensen, Rasmus & Friborg, Thomas, 2021. 12 p.Research output: Contribution to conference › Paper › Research
- Published
Prediction of above ground biomass and C-stocks based on UAV-LiDAR,multispectral imagery and machine learning methods.
Revenga, J. C., Trepekli, Aikaterini, Oehmcke, Stefan, Gieseke, Fabian Cristian, Jensen, Rasmus & Friborg, Thomas, 2021. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
ID: 209373892
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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
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37
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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 › peer-review
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Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale
Research output: Contribution to journal › Journal article › peer-review
Published