Stefan Oehmcke
Assistant Professor
- 2021
- Published
Prediction of above ground biomass and C-stocks based on UAV-LiDAR,multispectral imagery and machine learning methods.
Caballer Revenga, Jaime, 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
- 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 › 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, Caballer Revenga, Jaime, Oehmcke, Stefan, Gieseke, Fabian Cristian, Jensen, Rasmus & Friborg, Thomas, 2021. 12 p.Research output: Contribution to conference › Paper › Research
- 2020
- Published
Attention as activation
Dai, Y., Oehmcke, Stefan, Gieseke, Fabian Cristian, Wu, Y. & Barnard, K., 2020, Proceedings of ICPR 2020 - 25th International Conference on Pattern Recognition. IEEE, p. 4131-4136 6 p. 9413020Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Creating cloud-free satellite imagery from image time series with deep learning
Oehmcke, Stefan, Chen, T. H. K., Prishchepov, Alexander V. & Gieseke, Fabian Cristian, 3 Nov 2020, Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BIGSPATIAL 2020. Chandola, V., Vatsavai, R. R. & Shashidharan, A. (eds.). Association for Computing Machinery, 10 p. 3Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2019
- Published
Magnitude and Uncertainty Pruning Criterion for Neural Networks
Ko, V., Oehmcke, Stefan & Gieseke, Fabian Cristian, 2019, 2019 IEEE International Conference on Big Data, Big Data. Baru, C., Huan, J., Khan, L., Hu, X. T., Ak, R., Tian, Y., Barga, R., Zaniolo, C., Lee, K. & Ye, Y. F. (eds.). IEEE, p. 2317-2326 9005692. (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data
Oehmcke, Stefan, Thrysøe, C., Borgstad, A., Vaz Salles, M. A., Brandt, Martin Stefan & Gieseke, Fabian Cristian, 2019, Proceedings of the IEEE International Conference on Big Data, Big Data 2019: Special Session on Intelligent Data Mining. IEEE, p. 2403-2412 9006251,Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Evolution of Stacked Autoencoders
Silhan, T., Oehmcke, Stefan & Kramer, O., 2019, 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 823-830 8 p. 8790182Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2018
Direct training of dynamic observation noise with UMarineNet
Oehmcke, Stefan, Zielinski, O. & Kramer, O., 1 Jan 2018, Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, 2018, Proceedings. Kurkova, V., Hammer, B., Manolopoulos, Y., Iliadis, L. & Maglogiannis, I. (eds.). Springer Verlag, p. 123-133 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11139 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Input quality aware convolutional LSTM networks for virtual marine sensors
Oehmcke, Stefan, Zielinski, O. & Kramer, O., 31 Jan 2018, In: Neurocomputing. 275, p. 2603-2615 13 p.Research output: Contribution to journal › Journal article › 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 -
107
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 -
70
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