Soft electronic material based sensor with optical network in sports application for player movement analysis using machine learning model
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11082-023-06095-8.pdf
Reference20 articles.
1. Bocu, R., Bocu, D., Iavich, M.: An extended review concerning the relevance of deep learning and privacy techniques for data-driven soft sensors. Sensors 23(1), 294 (2022)
2. Fu, M., Zhong, Q., Dong, J.: Sports action recognition based on deep learning and clustering extraction algorithm. Comput. Intell. Neurosci. 2022 (2022)
3. Gentner, N., Carletti, M., Kyek, A., Susto, G.A., Yang, Y.: DBAM: Making virtual metrology/soft sensing with time series data scalable through deep learning. Control. Eng. Pract. 116, 104914 (2021)
4. Guo, R., Liu, H., Xie, G., Zhang, Y., Liu, D.: A self-interpretable soft sensor based on deep learning and multiple attention mechanism: from data selection to sensor modeling. IEEE Trans. Ind. Inf. 19, 6859 (2022)
5. Huang, C., Jiang, L.: Data monitoring and sports injury prediction model based on embedded system and machine learning algorithm. Microprocess. Microsyst. 81, 103654 (2021)
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