Fabian Cristian Gieseke

Fabian Cristian Gieseke

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  1. Udgivet

    A framework for data mining in wind power time series

    Kramer, O., Gieseke, Fabian Cristian, Heinermann, J., Poloczek, J. & Treiber, N. A., 2014, Data analytics for renewable energy integration: Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers. Woon, W. L., Aung, Z. & Madnick, S. (red.). Springer, s. 97-107 (Lecture notes in computer science, Bind 8817).

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  2. A stochastic optimization approach for unsupervised kernel regression

    Kramer, O. & Gieseke, Fabian Cristian, 2011, Proceedings of the 2011 International Conference on Genetic and Evolutionary Methods: GEM 2011. CSREA Press, s. 111-115 5 s.

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  3. An efficient many-core implementation for semi-supervised support vector machines

    Gieseke, Fabian Cristian, 2015, Machine Learning, Optimization, and Big Data: First International Workshop, MOD 2015, Taormina, Sicily, Italy, July 21-23, 2015, Revised Selected Papers. Pardalos, P., Pavone, M., Farinella, G. M. & Cutello, V. (red.). Springer, s. 145-157 13 s. (Lecture notes in computer science, Bind 9432).

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  4. Analysis of wind energy time series with kernel methods and neural networks

    Kramer, O. & Gieseke, Fabian Cristian, 2011, Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011. IEEE, Bind 4. s. 2381-2385 5 s. 6022597

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  5. Analyzing complex and structured data via unsupervised learning techniques

    Polsterer, K. L., Gieseke, Fabian Cristian, Gianniotis, N. & Kügler, D., 2015.

    Publikation: Konferencebidrag › Paper › Forskning

  6. Udgivet

    Approximate Nearest-Neighbour Fields via Massively-Parallel Propagation-Assisted K-D Trees

    Oancea, Cosmin Eugen, Robroek, T. & Gieseke, Fabian Cristian, 2020, Proceedings of the IEEE International Conference on Big Data (BigData2020). 10 udg. IEEE, s. 5172-5181

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  7. Udgivet

    Artistic movement recognition by boosted fusion of color structure and topographic description

    Florea, C., Toca, C. & Gieseke, Fabian Cristian, 11 maj 2017, Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision. IEEE, s. 569-577 9 s.

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  8. Udgivet

    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. 9413020

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  9. Udgivet

    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. 3559-3568

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  10. Udgivet

    Automatic galaxy classification via machine learning techniques: Parallelized rotation/flipping INvariant Kohonen maps (PINK)

    Polsterer, K. L., Gieseke, Fabian Cristian & Igel, Christian, 2015, Astronomical Data Analysis Software and Systems: Proceedings of a meeting held at Calgary, Alberta, Canada 5-9 October 2014. Taylor, A. R. & Rosolowsky, E. (red.). Astronomical Society of the Pacific, Bind 24. s. 81-86 6 s. (ASP Conference Series, Bind 495).

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

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