Stefan Oehmcke
Assistant Professor
Recurrent neural networks and exponential PAA for virtual marine sensors
Oehmcke, Stefan, Zielinski, O. & Kramer, O., 30 Jun 2017, 2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 4459-4466 8 p. 7966421Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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
- Published
More than one quarter of Africa's tree cover is found outside areas previously classified as forest
Reiner, F., Brandt, M., Tong, X., Skole, D., Kariryaa, A., Ciais, P., Davies, A., Hiernaux, P., Chave, J., Mugabowindekwe, M., Igel, C., Oehmcke, S., Gieseke, F., Li, S., Liu, S., Saatchi, S., Boucher, P., Singh, J., Taugourdeau, S., Dendoncker, M. & 4 others, , 2023, In: Nature Communications. 14, 10 p., 2258.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
Caballer Revenga, Jaime, Trepekli, Aikaterini, Oehmcke, Stefan, Jensen, Rasmus, Li, Lei, Igel, Christian, Gieseke, Fabian Cristian & Friborg, Thomas, 2022, In: Remote Sensing. 14, 16, 22 p., 3912.Research output: Contribution to journal › Journal article › Research › peer-review
- 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
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
- 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
- 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
Spatio-temporal wind power prediction using recurrent neural networks
Woon, W. L., Oehmcke, Stefan & Kramer, O., 1 Jan 2017, Neural Information Processing - 24th International Conference, ICONIP 2017, Proceedings. Zhao, D., Li, Y., El-Alfy, E-S. M., Liu, D. & Xie, S. (eds.). Springer Verlag, p. 556-563 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10638 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › 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
LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing
Zhang, T., Li, Lei, Igel, Christian, Oehmcke, Stefan, Gieseke, F. & Peng, Z., 2023, 2022 IEEE International Conference on Computer and Communications (ICCC), Chengdu, China. IEEE, p. 1951-1957Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 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
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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106
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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
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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