This work is licensed under the Creative Commons Attribution 4.0 International License.
Xie, R. (2021). Intangible cultural heritage high-definition digital mobile display technology based on vr virtual visualization. Mobile Information Systems.Search in Google Scholar
Xu, Q., Liu, H., Liu, Y., & Wu, S. (2021). Innovative design of intangible cultural heritage elements in fashion design based on interactive evolutionary computation. Mathematical Problems in Engineering.Search in Google Scholar
Lvping, S. (2021). Blockchain technology for management of intangible cultural heritage. Scientific programming(Pt.12), 2021.Search in Google Scholar
Qi, Z. Y. (2019). Pilot study of applying creative computing for the activation of intangible cultural heritage. International Journal of Performability Engineering, 15(2).Search in Google Scholar
Li, Y., & Duan, P. (2019). Research on the innovation of protecting intangible cultural heritage in the “internet plus” era. Procedia Computer Science, 154, 20-25.Search in Google Scholar
Shi, M., Zhang, L., Yang, H., Zhang, G., & Qi, Y. (2019). Pilot study of applying creative computing for the activation of intangible cultural heritage. International Journal of Performability Engineering(2), 15.Search in Google Scholar
Zhao, X., & Jiang, Y. (2022). Synchronously improving multi-user english translation ability by using ai. International Journal on Artificial Intelligence Tools.Search in Google Scholar
Li, P., Ning, Y., & Fang, H. (2021). Artificial intelligence translation under the influence of multimedia teaching to study english learning mode. International Journal of Electrical Engineering Education, 002072092098352.Search in Google Scholar
Li, Z. (2021). Artificial intelligence machine translation based on fuzzy algorithm. Mobile information systems.Search in Google Scholar
Choi, H., Cho, K., & Bengio, Y. (2018). Fine-grained attention mechanism for neural machine translation. NEUROCOMPUTING, 284(APR.5), 171-176.Search in Google Scholar
Karakanta, A., Dehdari, J., & Van Genabith, J. (2017). Neural machine translation for low-resource languages without parallel corpora. Machine Translation.Search in Google Scholar
Linying, Z., & Qiang, S. (2017). Research on english machine translation based on the basic word analysis. Revista de la Facultad de Ingenieria, 32(16), 58-65.Search in Google Scholar
Nonaka, K., Yamanouchi, K., Tomohiro, I., Okita, T., Shimada, K., & Sakamoto, H. (2022). A compression-based multiple subword segmentation for neural machine translation. Electronics, 11(7), 1014-.Search in Google Scholar
Lee, Y. H., Shin, J. H., & Kim, Y. K. (2021). Simultaneous neural machine translation with a reinforced attention mechanism. ETRI Journal, 43.Search in Google Scholar
Nguyen, L. H. B., Pham, V. H., & Dinh, D. (2021). Improving neural machine translation with amr semantic graphs. ICIC Express Letters.¥Search in Google Scholar
Zamora-Martinez, F., & Castro-Bleda, M. J. (2018). Efficient embedded decoding of neural network language models in a machine translation system. International Journal of Neural Systems, 1850007.Search in Google Scholar
Tan, Z., Su, J., Wang, B., Chen, Y., & Shi, X. (2018). Lattice-to-sequence attentional neural machine translation models. Neurocomputing, 284(APR.5), 138–147.Search in Google Scholar
Chua, C. C., Lim, T. Y., Soon, L. K., Tang, E. K., & Ranaivo-Malan?On, B. (2017). Meaning preservation in example-based machine translation with structural semantics. Expert Systems with Applications, 78(JUL.), 242-258.Search in Google Scholar
Zhao, Y., Komachi, M., Kajiwara, T., & Chu, C. (2022). Region-attentive multimodal neural machine translation. Neurocomputing, 476, 1-13.Search in Google Scholar
Fan, D., Xiao, F., & Tang, D. (2019). A new erasure code decoding algorithm. International Journal of Network Security, 21(3), 522-529.Search in Google Scholar
Kaya, Heysem, Karpov, Alexey, & A. (2018). Efficient and effective strategies for cross-corpus acoustic emotion recognition. Neurocomputing.Search in Google Scholar