Stefan Oehmcke
Adjunkt
Analysis of diversity methods for evolutionary multi-objective ensemble classifiers
Oehmcke, Stefan, Heinermann, J. & Kramer, O., 1 jan. 2015, Applications of Evolutionary Computation - 18th European Conference, EvoApplications 2015, Proceedings. Squillero, G. & Mora, A. M. (red.). Springer Verlag, s. 567-578 12 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 9028).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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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, s. 4131-4136 6 s. 9413020Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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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, s. 3559-3568Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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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. (red.). Association for Computing Machinery, 10 s. 3Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Deep learning based 3D point cloud regression for estimating forest biomass
Oehmcke, Stefan, Li, Lei, Caballer Revenga, Jaime, Nord-Larsen, Thomas, Trepekli, Aikaterini, Gieseke, F. & Igel, Christian, 1 nov. 2022, 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2022. Renz, M., Sarwat, M., Nascimento, M. A., Shekhar, S. & Xie, X. (red.). Association for Computing Machinery, Inc., s. 1-4 38Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
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, s. 2403-2412 9006251,Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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. (red.). Springer Verlag, s. 123-133 11 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11139 LNCS).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
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. (red.). Ljubljana: Jožef Stefan Institute , s. 13-19 7 s.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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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. (red.). Institute of Electrical and Electronics Engineers Inc., s. 4915-4924 10 s.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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. (red.). Springer Verlag, s. 279-286 8 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 9324).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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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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