Xu, W.; He, J.; Li, W.; He, Y.; Wan, H.; Qin, W.; Chen, Z.
Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices. Sensors 2023, 23, 7874.
https://doi.org/10.3390/s23187874
AMA Style
Xu W, He J, Li W, He Y, Wan H, Qin W, Chen Z.
Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices. Sensors. 2023; 23(18):7874.
https://doi.org/10.3390/s23187874
Chicago/Turabian Style
Xu, Weidong, Jingke He, Weihua Li, Yi He, Haiyang Wan, Wu Qin, and Zhuyun Chen.
2023. "Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices" Sensors 23, no. 18: 7874.
https://doi.org/10.3390/s23187874
APA Style
Xu, W., He, J., Li, W., He, Y., Wan, H., Qin, W., & Chen, Z.
(2023). Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices. Sensors, 23(18), 7874.
https://doi.org/10.3390/s23187874
