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  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2987573

  Grimmelsmann, N., Mechtenberg, M., Vieth, M., Schulz, A., Hammer, B., & Schneider, A. (2024). Predicting the Level of Co-Activation of One Muscle Head from the Other Muscle Head of the Biceps Brachii Muscle by Linear Regression and Shallow Feedforward Neural Networks. Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies, 611-621. Setúbal, Portugal: SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0012368700003657

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• [2]
  

  2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983250

  Vieth, M., Schulz, A., & Hammer, B. (2023). Extending Drift Detection Methods to Identify When Exactly the Change Happened. In I. Rojas, G. Joya, & A. Catala (Eds.), Lecture Notes in Computer Science. Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part I (pp. 92-104). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43085-5_8

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  2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2967410

  Vieth, M., Grimmelsmann, N., Schneider, A., & Hammer, B. (2022). Efficient Sensor Selection for Individualized Prediction Based on Biosignals. In H. Yin, D. Camacho, & P. Tino (Eds.), Lecture Notes in Computer Science: Vol. 13756. Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings (pp. 326-337). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-21753-1_32

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