10 Publikationen
2024 | Konferenzbeitrag | FH-PUB-ID: 4644
Klein, L., Ostrau, C., Thies, M., Schenck, W., & Rückert, U. (2024). Exploratory Analysis of Machine Learning Methods for the Prognosis of Falls in Elderly Care Based on Accelerometer Data. In D. Salvi, P. Van Gorp, & S. A. Shah (Eds.), Pervasive Computing Technologies for Healthcare. 17th EAI International Conference, PervasiveHealth 2023, Malmö, Sweden, November 27-29, 2023, Proceedings (pp. 423–437). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-59717-6_27
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2024 | Artikel | FH-PUB-ID: 4626 | 
Pottharst, B., Neumann, A., Ostrau, C., & Seelmeyer, U. (2024). Bewältigung des Fachkräftemangels durch technologische Innovation? Sozial Extra. https://doi.org/10.1007/s12054-024-00694-9
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2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 4639 |
Herzig, T. C., Marschner, C., Held, S., Jungeblut, T., Baudisch, J., Ostrau, C., … Nauerth, A. (2024). KI-gestütztes Monitoring zur Unterstützung in der häuslichen Pflege (KIMUP) . In Institute for Data Science Solutions (Ed.), Kongress KI@HSBI2023 Solutions im Fokus - Posterbeiträge (Vol. 1, pp. 9–10). Bielefeld: Hochschule Bielefeld. https://doi.org/10.60802/sidas.2024.1
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2022 | Artikel | FH-PUB-ID: 2639 |
Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2022). Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience, 16. https://doi.org/10.3389/fnins.2022.873935
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2022 | Dissertation | FH-PUB-ID: 2640 |
Ostrau, C. (2022). Energy and Performance Estimation for Neuromorphic Systems. Universität Bielefeld. https://doi.org/10.4119/UNIBI/2962759
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2020 | Konferenzbeitrag | FH-PUB-ID: 2668
Ostrau, C., Homburg, J., Klarhorst, C., Thies, M., & Rückert, U. (2020). Benchmarking Deep Spiking Neural Networks on Neuromorphic Hardware. In I. Farkaš, P. Masulli, & S. Wermter (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2020. 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part II (pp. 610–621). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-61616-8_49
HSBI-PUB
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2020 | Konferenzbeitrag | FH-PUB-ID: 2642
Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2020). Benchmarking of Neuromorphic Hardware Systems. In Proceedings of the Neuro-inspired Computational Elements Workshop (pp. 1–4). New York, NY, USA: ACM. https://doi.org/10.1145/3381755.3381772
HSBI-PUB
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2019 | Kurzbeitrag Konferenz | FH-PUB-ID: 2669 |
Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2019). Benchmarking and Characterization of event-based Neuromorphic Hardware . Presented at the FastPath 2019 - International Workshop on Performance Analysis of Machine Learning Systems, Madison, Wisconsin, USA.
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2019 | Konferenzbeitrag | FH-PUB-ID: 2643
Ostrau, C., Klarhorst, C., Thies, M., & Ruckert, U. (2019). Comparing Neuromorphic Systems by Solving Sudoku Problems. In 2019 International Conference on High Performance Computing & Simulation (HPCS) (pp. 521–527). Dublin, Ireland: IEEE. https://doi.org/10.1109/HPCS48598.2019.9188207
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2017 | Artikel | FH-PUB-ID: 2644 |
Stöckel, A., Jenzen, C., Thies, M., & Rückert, U. (2017). Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware. Frontiers in Computational Neuroscience, 11. https://doi.org/10.3389/fncom.2017.00071
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10 Publikationen
2024 | Konferenzbeitrag | FH-PUB-ID: 4644
Klein, L., Ostrau, C., Thies, M., Schenck, W., & Rückert, U. (2024). Exploratory Analysis of Machine Learning Methods for the Prognosis of Falls in Elderly Care Based on Accelerometer Data. In D. Salvi, P. Van Gorp, & S. A. Shah (Eds.), Pervasive Computing Technologies for Healthcare. 17th EAI International Conference, PervasiveHealth 2023, Malmö, Sweden, November 27-29, 2023, Proceedings (pp. 423–437). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-59717-6_27
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 4626 |
Pottharst, B., Neumann, A., Ostrau, C., & Seelmeyer, U. (2024). Bewältigung des Fachkräftemangels durch technologische Innovation? Sozial Extra. https://doi.org/10.1007/s12054-024-00694-9
HSBI-PUB
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| DOI
| Download (ext.)
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 4639 |
Herzig, T. C., Marschner, C., Held, S., Jungeblut, T., Baudisch, J., Ostrau, C., … Nauerth, A. (2024). KI-gestütztes Monitoring zur Unterstützung in der häuslichen Pflege (KIMUP) . In Institute for Data Science Solutions (Ed.), Kongress KI@HSBI2023 Solutions im Fokus - Posterbeiträge (Vol. 1, pp. 9–10). Bielefeld: Hochschule Bielefeld. https://doi.org/10.60802/sidas.2024.1
HSBI-PUB
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2022 | Artikel | FH-PUB-ID: 2639 |
Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2022). Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience, 16. https://doi.org/10.3389/fnins.2022.873935
HSBI-PUB
| DOI
| Download (ext.)
2022 | Dissertation | FH-PUB-ID: 2640 |
Ostrau, C. (2022). Energy and Performance Estimation for Neuromorphic Systems. Universität Bielefeld. https://doi.org/10.4119/UNIBI/2962759
HSBI-PUB
| DOI
| Download (ext.)
2020 | Konferenzbeitrag | FH-PUB-ID: 2668
Ostrau, C., Homburg, J., Klarhorst, C., Thies, M., & Rückert, U. (2020). Benchmarking Deep Spiking Neural Networks on Neuromorphic Hardware. In I. Farkaš, P. Masulli, & S. Wermter (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2020. 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part II (pp. 610–621). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-61616-8_49
HSBI-PUB
| DOI
2020 | Konferenzbeitrag | FH-PUB-ID: 2642
Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2020). Benchmarking of Neuromorphic Hardware Systems. In Proceedings of the Neuro-inspired Computational Elements Workshop (pp. 1–4). New York, NY, USA: ACM. https://doi.org/10.1145/3381755.3381772
HSBI-PUB
| DOI
2019 | Kurzbeitrag Konferenz | FH-PUB-ID: 2669 |
Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2019). Benchmarking and Characterization of event-based Neuromorphic Hardware . Presented at the FastPath 2019 - International Workshop on Performance Analysis of Machine Learning Systems, Madison, Wisconsin, USA.
HSBI-PUB
| Download (ext.)
2019 | Konferenzbeitrag | FH-PUB-ID: 2643
Ostrau, C., Klarhorst, C., Thies, M., & Ruckert, U. (2019). Comparing Neuromorphic Systems by Solving Sudoku Problems. In 2019 International Conference on High Performance Computing & Simulation (HPCS) (pp. 521–527). Dublin, Ireland: IEEE. https://doi.org/10.1109/HPCS48598.2019.9188207
HSBI-PUB
| DOI
2017 | Artikel | FH-PUB-ID: 2644 |
Stöckel, A., Jenzen, C., Thies, M., & Rückert, U. (2017). Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware. Frontiers in Computational Neuroscience, 11. https://doi.org/10.3389/fncom.2017.00071
HSBI-PUB
| DOI
| Download (ext.)