Stefan Oehmcke

Stefan Oehmcke

Assistant Professor

Member of:

    ORCID: 0000-0002-0240-1559

    Publication year:
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    21 - 30 out of 38Page size: 10
    1. 2021
    2. Published

      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. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 4915-4924 10 p.

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    3. 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

    4. 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

    5. 2020
    6. Published

      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. (eds.). Association for Computing Machinery, 10 p. 3

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    7. Published

      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, p. 4131-4136 6 p. 9413020

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    8. 2019
    9. Published

      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, p. 2403-2412 9006251,

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    10. 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. 8790182

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    11. 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

    12. 2018

    13. Input quality aware convolutional LSTM networks for virtual marine sensors

      Oehmcke, Stefan, Zielinski, O. & Kramer, O., 31 Jan 2018, In: Neurocomputing. 275, p. 2603-2615 13 p.

      Research output: Contribution to journal › Journal article › Research › peer-review

    14. 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

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