Stefan Oehmcke
Assistant Professor
ORCID: 0000-0002-0240-1559
1 - 2 out of 2Page 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
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
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
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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 › Research › peer-review
Published -
69
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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 › Research › peer-review
Published