Stefan Oehmcke
Adjunkt
- Udgivet
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. (red.). IEEE, s. 5914-5923 10 s.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
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., s. 823-830 8 s. 8790182Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
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, I: EPJ Data Science. 10, 1, 21 s., 44.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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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 s.Publikation: Konferencebidrag › Paper › Forskning
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. (red.). Springer Verlag, s. 556-563 8 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 10638 LNCS).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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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. (red.). Association for Computing Machinery, Inc., s. 52-60Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
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, s. 1951-1957Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Multi-scale pseudo labeling for unsupervised deep edge detection
Zhou, C., Yuan, C., Wang, H., Li, Lei, Oehmcke, Stefan, Liu, J. & Peng, J., 2023, I: Knowledge-Based Systems. 280, 15 s., 111057.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
ID: 209373892
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Creating cloud-free satellite imagery from image time series with deep learning
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Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale
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Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
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