Stefan Oehmcke
Assistant Professor
Knowledge sharing for population based neural network training
Oehmcke, Stefan & Kramer, O., 1 Jan 2018, KI 2018: Advances in Artificial Intelligence - 41st German Conference on AI, 2018, Proceedings. Turhan, A-Y. & Trollmann, F. (eds.). Springer Verlag, p. 258-269 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11117 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Event detection in marine time series data
Oehmcke, Stefan, Zielinski, O. & Kramer, O., 1 Jan 2015, KI 2015: Advances in Artificial Intelligence - 38th Annual German Conference on AI, Proceedings. Hölldobler, S., Krötzsch, M., Rudolph, S. & Peñaloza, R. (eds.). Springer Verlag, p. 279-286 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 9324).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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
Manifold learning with iterative dimensionality photo-projection
Luckehe, D., Oehmcke, Stefan & Kramer, O., 30 Jun 2017, 2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 2555-2561 7 p. 7966167Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale
Li, Sizhuo, Brandt, Martin Stefan, Fensholt, Rasmus, Kariryaa, Ankit, Igel, Christian, Gieseke, Fabian Cristian, Nord-Larsen, Thomas, Oehmcke, Stefan, Carlsen, Ask Holm, Junttila, S., Tong, Xiaoye, d’Aspremont, A. & Ciais, P., 2023, In: PNAS Nexus. 2, 4, 16 p., pgad076.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Satellite-based continental-scale inventory of European wetland types at 10m spatial resolution
Kovács, Gyula Mate, Oehmcke, Stefan, Horion, Stéphanie, Gominski, Dimitri Pierre Johannes, Tong, Xiaoye & Fensholt, Rasmus, 2023. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
- 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
Remember to Correct the Bias When Using Deep Learning for Regression!
Igel, Christian & Oehmcke, Stefan, 2023, In: KI - Kunstliche Intelligenz. 37, 1, p. 33-40Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Ensemble Learning for Semantic Segmentation of Ancient Maya Architectures
Hellweg, Thorben, Oehmcke, Stefan, Kariryaa, Ankit, Gieseke, Fabian Cristian & Igel, Christian, 2022, Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & the Discovery Challenge Workshop, ECML PKDD 2021. Kocev, D., Simidjievski, N., Kostovska, A., Dimitrovski, I. & Kokalj, Ž. (eds.). Ljubljana: Jožef Stefan Institute , p. 13-19 7 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › 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
Published -
107
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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 -
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