Stefan Oehmcke

Publikation

Publikationer pr. år 2015 2023 2024

• 906 Citationer
• 22 Konferencebidrag i proceedings
• 12 Tidsskriftartikel
• 5 Konferenceabstrakt til konference
• 1 Paper
• 1 Mere
  • 1 Preprint

Publikationer pr. år

Publikationer pr. år

Søgeresultater

• 2024

  Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR

  Oehmcke, S., Li, L., Trepekli, K., Revenga, J. C., Nord-Larsen, T., Gieseke, F. & Igel, C., 2024, I: Remote Sensing of Environment. 302, 21 s., 113968.

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  9 Citationer (Scopus)

  57 Downloads (Pure)

• Global mapping of human-transformed dike-pond systems

  Xu, Y., Feng, L., Fang, H., Song, X-P., Gieseke, F., Kariryaa, A., Oehmcke, S., Gibson, L., Jiang, X., Lin, R., Woolway, R. I., Zheng, C., Brandt, M. & Fensholt, R., 2024, I: Remote Sensing of Environment. 313, 14 s., 114354.

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  2 Citationer (Scopus)

• High-resolution mapping of tree mortality in European forests

  Cheng, Y., Oehmcke, S., Mosig, C., Beloiu, M., Kattenborn, T., Abel, C., Gominski, D. P. J., Nord-Larsen, T., Fensholt, R. & Horion, S., 2024. 1 s.

  Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › peer review

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• Modelling Residential Fire Vulnerability of Denmark

  Crump, N., Markussen, B., Oehmcke, S., Igel, C., Skov-Petersen, H. & Karlsson Nyed, P., 2024, (E-pub ahead of print) I: Fire Technology.

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• Scattered tree death contributes to substantial forest loss in California

  Cheng, Y., Oehmcke, S., Brandt, M. S., Rosenthal, L., Das, A., Vrieling, A., Saatchi, S., Wagner, F., Mugabowindekwe, M., Verbruggen, W., Beier, C. & Horion, S., 2024, I: Nature Communications. 15, 1, s. 1-13 641.

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  3 Citationer (Scopus)

  38 Downloads (Pure)
• 2023

  BuildSeg: A General Framework for the Segmentation of Buildings

  Li, L., Zhang, T., Oehmcke, S., Gieseke, F. & Igel, C., 15 jan. 2023, arxiv.org, 7 s.

  Publikation: Working paper › Preprint › Forskning

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• Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale

  Li, S., Brandt, M., Fensholt, R., Kariryaa, A., Igel, C., Gieseke, F., Nord-Larsen, T., Oehmcke, S., Carlsen, A. H., Junttila, S., Tong, X., d’Aspremont, A. & Ciais, P., 2023, I: PNAS Nexus. 2, 4, 16 s., pgad076.

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  23 Citationer (Scopus)

  132 Downloads (Pure)

• High nitrous oxide emissions from temporary flooded depressions within croplands

  Elberling, B., Kovács, G. M., Hansen, H. F. E., Fensholt, R., Ambus, P., Tong, X., Gominski, D., Mueller, C. W., Poultney, D. M. N. & Oehmcke, S., 2023, I: Communications Earth and Environment. 4, 1, 9 s., 463.

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• LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing

  Zhang, T., Li, L., Igel, C., Oehmcke, S., Gieseke, F. & Peng, Z., 2023, 2022 IEEE International Conference on Computer and Communications (ICCC), Chengdu, China. IEEE, s. 1951-1957

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  7 Citationer (Scopus)

  13 Downloads (Pure)

• Mapping and characterising tree mortality in California at individual tree level using deep learning

  Cheng, Y., Oehmcke, S., Brandt, M., Das, A., Rosenthal, L., Saatchi, S., Wagner, F., Verbruggen, W., Vrieling, A., Beier, C. & Horion, S., 2023. 1 s.

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• MAPPING TREE MORTALITY IN CALIFORNIA FROM VERY HIGH RESOLUTION IMAGERY USING DEEP LEARNING

  Cheng, Y., Oehmcke, S., Brandt, M. S., Das, A., Rosenthal, L., Saatchi, S., Wagner, F., Vrieling, A., Verbruggen, W., Beier, C. & Horion, S., 2023.

  Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › peer review

• 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 flere, Song, X-P., Mertz, O., Tucker, C. J. & Fensholt, R., 2023, I: Nature Communications. 14, 10 s., 2258.

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  47 Citationer (Scopus)

  52 Downloads (Pure)

• Multi-scale pseudo labeling for unsupervised deep edge detection

  Zhou, C., Yuan, C., Wang, H., Li, L., Oehmcke, S., Liu, J. & Peng, J., 2023, I: Knowledge-Based Systems. 280, 15 s., 111057.

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  3 Citationer (Scopus)

  22 Downloads (Pure)

• Predicting urban tree cover from incomplete point labels and limited background information

  Zhang, H., Kariryaa, A., Guthula, V. B., Igel, C. & Oehmcke, S., 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. 52-60

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• Remember to Correct the Bias When Using Deep Learning for Regression!

  Igel, C. & Oehmcke, S., 2023, I: KI - Kunstliche Intelligenz. 37, 1, s. 33-40

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  2 Citationer (Scopus)

  16 Downloads (Pure)

• Satellite-based continental-scale inventory of European wetland types at 10m spatial resolution

  Kovács, G. M., Oehmcke, S., Horion, S., Gominski, D., Tong, X. & Fensholt, R., 2023. 1 s.

  Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › peer review

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• Seasonal-Trend Time Series Decomposition on Graphics Processing Units

  Serykh, D., Oehmcke, S., Oancea, C., Masiliunas, D., Verbesselt, J., Cheng, Y., Horion, S., Gieseke, F. & Hinnerskov, N., 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.

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• 2022

  Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods

  Revenga, J. C., Trepekli, K., Oehmcke, S., Jensen, R., Li, L., Igel, C., Gieseke, F. C. & Friborg, T., 2022, I: Remote Sensing. 14, 16, 22 s., 3912.

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  15 Citationer (Scopus)

  79 Downloads (Pure)

• Deep learning based 3D point cloud regression for estimating forest biomass

  Oehmcke, S., Li, L., Revenga, J. C., Nord-Larsen, T., Trepekli, K., Gieseke, F. & Igel, C., 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 38

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  9 Citationer (Scopus)

• Ensemble Learning for Semantic Segmentation of Ancient Maya Architectures

  Hellweg, T., Oehmcke, S., Kariryaa, A., Gieseke, F. & Igel, C., 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.

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• Input Selection for Bandwidth-Limited Neural Network Inference

  Oehmcke, S. & Gieseke, F., 2022, Proceedings of the 2022 SIAM International Conference on Data Mining, SDM 2022. SIAM, s. 280-288 9 s.

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  13 Downloads (Pure)
• 2021

  Attentional feature fusion

  Dai, Y., Gieseke, F., Oehmcke, S., Wu, Y. & Barnard, K., 2021, Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021. IEEE, s. 3559-3568

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  604 Citationer (Scopus)

• 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, S. & Andersen, I. G., 2021, I: EPJ Data Science. 10, 1, 21 s., 44.

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  3 Citationer (Scopus)

  18 Downloads (Pure)

• Estimating Forest Canopy Height with Multi-Spectral and Multi-Temporal Imagery Using Deep Learning

  Oehmcke, S., Nyegaard-Signori, T., Grogan, K. & Gieseke, F., 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.

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  1 Citationer (Scopus)

• Plant Structure and Carbon Storage Assessment Utilizing Drone-Borne Lidar and Deep Learning Technologies in a Danish Agricultural Expanse.

  Trepekli, K., Revenga, J. C., Oehmcke, S., Gieseke, F., Jensen, R. & Friborg, T., 2021. 12 s.

  Publikation: Konferencebidrag › Paper › Forskning

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• Prediction of above ground biomass and C-stocks based on UAV-LiDAR,multispectral imagery and machine learning methods.

  Revenga, J. C., Trepekli, K., Oehmcke, S., Gieseke, F., Jensen, R. & Friborg, T., 2021. 1 s.

  Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › peer review

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• 2020

  Attention as activation

  Dai, Y., Oehmcke, S., Gieseke, F., Wu, Y. & Barnard, K., 2020, Proceedings of ICPR 2020 - 25th International Conference on Pattern Recognition. IEEE, s. 4131-4136 6 s. 9413020

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  2 Citationer (Scopus)

• Creating cloud-free satellite imagery from image time series with deep learning

  Oehmcke, S., Chen, T. H. K., Prishchepov, A. V. & Gieseke, F., 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. 3

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  12 Citationer (Scopus)

  164 Downloads (Pure)
• 2019

  Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data

  Oehmcke, S., Thrysøe, C., Borgstad, A., Vaz Salles, M. A., Brandt, M. S. & Gieseke, F. C., 2019, Proceedings of the IEEE International Conference on Big Data, Big Data 2019: Special Session on Intelligent Data Mining. IEEE, s. 2403-2412 9006251,

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  16 Citationer (Scopus)

• Evolution of Stacked Autoencoders

  Silhan, T., Oehmcke, S. & Kramer, O., 2019, 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., s. 823-830 8 s. 8790182

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  7 Citationer (Scopus)

• Magnitude and Uncertainty Pruning Criterion for Neural Networks

  Ko, V., Oehmcke, S. & Gieseke, F., 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. (red.). IEEE, s. 2317-2326 9005692. (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).

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  4 Citationer (Scopus)
• 2018

  Direct training of dynamic observation noise with UMarineNet

  Oehmcke, S., 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).

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  1 Citationer (Scopus)

• Input quality aware convolutional LSTM networks for virtual marine sensors

  Oehmcke, S., Zielinski, O. & Kramer, O., 31 jan. 2018, I: Neurocomputing. 275, s. 2603-2615 13 s.

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  52 Citationer (Scopus)

• Knowledge sharing for population based neural network training

  Oehmcke, S. & Kramer, O., 1 jan. 2018, KI 2018: Advances in Artificial Intelligence - 41st German Conference on AI, 2018, Proceedings. Turhan, A-Y. & Trollmann, F. (red.). Springer Verlag, s. 258-269 12 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11117 LNAI).

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  2 Citationer (Scopus)
• 2017

  Manifold learning with iterative dimensionality photo-projection

  Luckehe, D., Oehmcke, S. & Kramer, O., 30 jun. 2017, 2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., s. 2555-2561 7 s. 7966167

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  3 Citationer (Scopus)

• Preferences-based choice prediction in evolutionary multi-objective optimization

  Aggarwal, M., Heinermann, J., Oehmcke, S. & Kramer, O., 1 jan. 2017, Applications of Evolutionary Computation - 20th European Conference, EvoApplications 2017, Proceedings. Hidalgo, J. I., Cotta, C., Hu, T., Tonda, A., Burrelli, P., Coler, M., Iacca, G., Kampouridis, M., Mora Garcia, A. M., Squillero, G., Brabazon, A., Haasdijk, E., Heinerman, J., D Andreagiovanni, F., Bacardit, J., Nguyen, T. T., Silva, S., Tarantino, E., Esparcia-Alcazar, A. I., Ascheid, G., Glette, K., Cagnoni, S., Kaufmann, P., de Vega, F. F., Mavrovouniotis, M., Zhang, M., Divina, F., Sim, K., Urquhart, N. & Schaefer, R. (red.). Springer Verlag, s. 715-724 10 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 10199 LNCS).

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  2 Citationer (Scopus)

• Recurrent neural networks and exponential PAA for virtual marine sensors

  Oehmcke, S., Zielinski, O. & Kramer, O., 30 jun. 2017, 2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., s. 4459-4466 8 s. 7966421

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  6 Citationer (Scopus)

• Spatio-temporal wind power prediction using recurrent neural networks

  Woon, W. L., Oehmcke, S. & 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).

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  3 Citationer (Scopus)
• 2016

  kNN ensembles with penalized DTW for multivariate time series imputation

  Oehmcke, S., Zielinski, O. & Kramer, O., 31 okt. 2016, 2016 International Joint Conference on Neural Networks, IJCNN 2016. Institute of Electrical and Electronics Engineers Inc., s. 2774-2781 8 s. 7727549

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  47 Citationer (Scopus)
• 2015

  Analysis of diversity methods for evolutionary multi-objective ensemble classifiers

  Oehmcke, S., 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).

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  4 Citationer (Scopus)

• Event detection in marine time series data

  Oehmcke, S., 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).

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  17 Citationer (Scopus)