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He, X., & Tian, S. (2022). Analysis of the Communication Method of National Traditional Sports Culture Based on Deep Learning. Scientific Programming, 2022(01), 9697014.Search in Google Scholar
Li, C., & Lyu, S. (2022). Machine Learning-Based Classification and Evaluation of Regional Ethnic Traditional Sports Tourism Resources. Mobile Information Systems, 2022(01), 8404931.Search in Google Scholar
Huang, G., Gong, Y., & Xu, Q. (2020). A Convolutional Attention Residual Network for Stereo Matching. IEEE Access, 8(1), 50828-50842.Search in Google Scholar
Sun, Z., Wang, X., & Zhang, Q. (2019). Real-Time Video Saliency Prediction Via 3D Residual Convolutional Neural Network. IEEE Access, 7(1), 147743-147754.Search in Google Scholar
Qing, Y., & Liu, W. (2021). Hyperspectral Image Classification Based on Multi-Scale Residual Network with Attention Mechanism. Remote Sensing, 13(3), 335.Search in Google Scholar
Dong, M., Fang, Z., & Li, Y. (2021). AR3D: Attention Residual 3D Network for Human Action Recognition. Sensors, 21(5), 1656.Search in Google Scholar
Cai, J., & Hu, J. (2020). 3D RANs: 3D Residual Attention Networks for action recognition. Visual Computer, 36(6), 1261-1270.Search in Google Scholar
Li, X., Zhou, Z., & Chen, L. (2019). Residual attention-based LSTM for video captioning. World Wide Web-Internet and Web Information Systems, 22(2), 621-636.Search in Google Scholar
Saab, S., Fu, Y., & Ray, A. (2022). A Dynamically Stabilized Recurrent Neural Network. Neural Processing Letters, 54(2), 1195-1209.Search in Google Scholar
Lyu, S., & Liu, J. (2021). Convolutional Recurrent Neural Networks for Text Classification. Journal of Database Management, 32(4), 65-82.Search in Google Scholar
Wu, H., & Prasad, S. (2017). Convolutional Recurrent Neural Networks for Hyperspectral Data Classification. Remote Sensing, 9(3), 298.Search in Google Scholar
Li, B., & Zhuang, X. (2020). Multiscale computation on feedforward neural network and recurrent neural network. Frontiers of Structural and Civil Engineering, 14(6), 1285-1298.Search in Google Scholar
Chen, Y. (2020). Voltages prediction algorithm based on LSTM recurrent neural network. Optik, 220(1), 164869.Search in Google Scholar
Mirza, A. H., Kerpicci, M., & Kozat, S. S. (2020). Efficient online learning with improved LSTM neural networks. Digital Signal Processing, 102(1), 102742.Search in Google Scholar
Zhu, X., Li, L., & Liu, J. (2018). Image captioning with triple-attention and stack parallel LSTM. Neurocomputing, 319(01), 55-65.Search in Google Scholar
Lashgari, E., Ott, J., & Connelly, A. (2021). An end-to-end CNN with attentional mechanism applied to raw EEG in a BCI classification task. Journal of Neural Engineering, 18(4), 0460e3.Search in Google Scholar
Chen, J., Du, L., & Guo, G. (2022). Target-attentional CNN for Radar Automatic Target Recognition with HRRP. Signal Processing, 196(01), 108497.Search in Google Scholar
Liu, A. A., Zhou, H. Y., & Li, M. J. (2020). 3D model retrieval based on multi-view attentional convolutional neural network. Multimedia Tools and Applications, 79(7-8), 4699-4711.Search in Google Scholar
Fan, Y. (2021). Disciplinary Construction and Cultivation System of Wushu and National Traditional Sports. Revista Brasileira De Medicina Do Esporte, 27(4), 395-399.Search in Google Scholar
Ai, X. B. (2022). Intelligent Integration Algorithm of National Traditional Sports Culture Resources Based on Big Data. Journal of Mathematics, 2022(01), 8335300.Search in Google Scholar
Feng, Q., Ren, B., & Wang, L. (2022). Smart Service System for Youth Health and National Traditional Sports Based on Big Data. Wireless Communications & Mobile Computing, 2022(01), 4094412.Search in Google Scholar
Yan, S., Wang, J., Ma, H. (2021). The Swot Analysis of the Development of Traditional National Sports Under the Environment of Population Aging. Fresenius Environmental Bulletin, 30(8), 9687-9695.Search in Google Scholar
Araujo, R., Mesquita, I., & Hastie, P. A. (2014). Review of the Status of Learning in Research on Sport Education: Future Research and Practice. Journal of Sports Science and Medicine, 13(4), 846-858.Search in Google Scholar
Guo, Q, & Li, B. (2021). Role of AI physical education based on application of functional sports training. Journal of Intelligent & Fuzzy Systems, 40(2), 3337-3345.Search in Google Scholar
Young, B. W., Rathwell, S., & Callary, B. (2020). Testing a coaching assessment tool derived from adult education in adult sport. Psychology of Sport and Exercise, 47(1), 101632.Search in Google Scholar
Yengo-Kahn, A. M., Hale, A. T., & Zalneraitis, B. H. (2016). The Sport Concussion Assessment Tool: a systematic review. Neurosurgical Focus, 40(4), E6.Search in Google Scholar
Bessa, C., Hastie, P., & Araujo, R. (2019). What Do We Know About the Development of Personal and Social Skills within the Sport Education Model: A Systematic Review. Journal of Sports Science and Medicine, 18(4), 812-829.Search in Google Scholar
Li, Y., & Li, X. (2022). The Artificial Intelligence System for the Generation of Sports Education Guidance Model and Physical Fitness Evaluation Under Deep Learning. Frontiers in Public Health, 10(1), 917053.Search in Google Scholar