Optimizing On-Body Sensor Placements for Deep Learning-Driven Human Activity Recognition
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64608-9_21
Reference28 articles.
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2. Alsarhan, T., Alawneh, L., Al-Zinati, M., Al-Ayyoub, M.: Bidirectional gated recurrent units for human activity recognition using accelerometer data. In: 2019 IEEE SENSORS, pp. 1–4 (2019). https://doi.org/10.1109/SENSORS43011.2019.8956560
3. Atallah, L., Lo, B., King, R., Yang, G.Z.: Sensor positioning for activity recognition using wearable accelerometers. IEEE Trans. Biomed. Circ. Syst. 5(4), 320–329 (2011). https://doi.org/10.1109/TBCAS.2011.2160540
4. Attal, F., Mohammed, S., Dedabrishvili, M., Chamroukhi, F., Oukhellou, L., Amirat, Y.: Physical human activity recognition using wearable sensors. Sensors 15(12), 31314–31338 (2015). https://doi.org/10.3390/s151229858
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