Open Access
SHS Web of Conferences
Volume 185, 2024
2024 2nd International Conference on Language and Cultural Communication (ICLCC 2024)
Article Number 01004
Number of page(s) 9
Section Research on Language Teaching and Text Reading
Published online 14 March 2024
  1. Jin, L.W., Zhong, Z.Y., Yang, Z., Yang, W.X., Xie, Z.C., Sun, J. (2016) Applications of Deep Learning for Handwritten Chinese Character Recognition: A Review. Acta Automatica Sinica, 42(8): 1125–1141. [Google Scholar]
  2. Zhang, B., Jin, L.W. (2017) Handwritten Chinese Similar Characters Recognition Based On AdaBoost. Proceedings of the 26th Chinese Control Conference. [Google Scholar]
  3. Nambu, H., Kawamata, T., Maruyama, F., Yoda, F. (1998) On-line Handwriting Chinese Character Recognition; Comparison and Improvement to Japanese Kanji Recognition. In: International Conference on Pattern Recognition. IEEE Computer Society. [Google Scholar]
  4. Chin, W., Kim, K. (2002) On-line Handwriting Chinese Character Recognition for PDA Using a Unit Reconstruction Method. Journal of the Institute of Electronics Engineers, 39(1): 97–107. [Google Scholar]
  5. Wang, Y.W., Liu, C.S., Ding X.Q. (2013) Similar Pattern Discriminant Analysis for Improving Chinese Character Recognition Accuracy. International Conference on Document Analysis & Recognition. IEEE. [Google Scholar]
  6. Yang, C., Wang, Q., Du, J., Zhang, J.S., Wu, C.J., Wang, J.M. (2021) A Transformer-based Radical Analysis Network for Chinese Character Recognition. In: 25th International Conference on Pattern Recognition (ICPR). Milan, Italy. 3714–3719. [Google Scholar]
  7. Kim, W.J., Choi, J.Y. (2023) Current Status and Prospects of Chinese Character Recognition Models in Korea. The Society for Korean Language & Literary Research, 51(4): 313–341. [Google Scholar]
  8. Wang, W.C., Zhang, J.S., Du, J., Wang, Z.R., Zhu, Y.X. (2018) DenseRAN for Offline Handwritten Chinese Character Recognition. IEEE, 16: 104–109. [Google Scholar]
  9. Xu, Q., Bai, X., Liu, W. (2019) Multiple Comparative Attention Network for Offline Handwritten Chinese Character Recognition. 2019 International Conference on Document Analysis and Recognition (ICDAR). 2019.6. [Google Scholar]
  10. Melnyk, P., You, Z.Q., Li, K.Q. (2020) A highperformance CNN method for offline handwritten Chinese character recognition and visualization. soft computing, 24(11), 7977–7987. [CrossRef] [Google Scholar]
  11. Li, Z., Wu, Q., Xiao, Y., Jin, M., Lu, H. (2020) Deep matching network for handwritten Chinese character recognition. Pattern Recognition, 107, 107471. [CrossRef] [Google Scholar]
  12. N. Aleskerova, A. Zhuravlev (2020) Handwritten Chinese Characters Recognition Using Two-Stage Hierarchical Convolutional Neural Network. In: 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR). Dortmund, Germany. 343–348. [Google Scholar]
  13. Cao, Z., Lu, J., Cui, S., & Zhang, C. (2020) Zero-shot Handwritten Chinese Character Recognition with hierarchical decomposition embedding. Pattern Recognition, 107, 107488. [CrossRef] [Google Scholar]
  14. Shi, P., Lou, Y., & Xia, R. (2023) Handwritten Chinese Character Recognition Based on Morphology and Transfer Learning. In 2023 International Conference on Intelligent Perception and Computer Vision (CIPCV), IEEE, 47–51. [Google Scholar]
  15. Li, Y.X., Yang, Q., Chen, Q.C., Hu, B.T., Wang, X.L., Ding, Y.X., Ma, L. (2022) Fast and Robust Online Handwritten Chinese Character Recognition with Deep Spatial & Contextual Information Fusion Network. IEEE Transactions on Multimedia. [Google Scholar]
  16. Yu, H., Chen, J., Li, B., & Xue, X. (2023) Chinese character recognition with radical-structured stroke trees. Machine Learning, 1–21. [Google Scholar]
  17. Du, Y.K., Liu, F.Q., Liu, Z.L. (2023) A novel multilevel stacked SqueezeNet model for handwritten Chinese character recognition. Computer Science and Information Systems, (00), 30–30. [Google Scholar]
  18. Gan, J., Chen, Y.Y., Hu, B., Leng, J.X., Wang, W.Q., Gao, X.B. (2023) Characters as graphs: Interpretable handwritten Chinese character recognition via Pyramid Graph Transformer. Pattern Recognition, 137, 109317. [CrossRef] [Google Scholar]
  19. Wang, T.W., Xie, Z.C., Li, Z., Jin, L.W., Chen, X.L. (2019) Radical aggregation network for few-shot offline handwritten Chinese character recognition. Pattern Recognition Letters, 125: 821–827. [CrossRef] [Google Scholar]
  20. Xiao, Y., Meng, D., Lu, C., & Tang, C. K. (2019) Template-instance loss for ofine handwritten Chinese character recognition. In 2019 International Conference on Document Analysis and Recognition (ICDAR), 315–322. [Google Scholar]
  21. Chen, Z., Yang, W., Li, X. (2023) Stroke-based autoencoders: Self-supervised learners for efcient zeroshot Chinese character recognition. Applied Sciences, 13(3), 1750. [CrossRef] [Google Scholar]
  22. Chen, J., Li, B., & Xue, X. (2021) Zero-shot Chinese character recognition with stroke-level decomposition. In Proceedings of the Thirtieth International Joint Conference on Artifcial Intelligence. [Google Scholar]
  23. Zu, X., Yu, H., Li, B., Xue, X. (2022) Chinese character recognition with augmented character profle matching. In Proceedings of the 30th ACM International Conference on Multimedia, 6094–6102. [Google Scholar]
  24. Wang, Y., Yang, Y., Ding, W., et al. (2021) A residual-attention offline handwritten Chinese text recognition based on fully convolutional neural networks, ” IEEE Access, Vol. 9, 132301–132310. [CrossRef] [Google Scholar]
  25. Peng, D., Jin, L., Liu, Y., et al. (2022) PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition. International Journal of Computer Vision, Vol. 130, No. 11, 2623–2645. [CrossRef] [Google Scholar]
  26. Xu, X., Yang, C., Wang, L., et al. (2022) A sophisticated offline network developed for recognizing handwritten Chinese character efficiently. Computers and Electrical Engineering, Vol. 100, 107857. [CrossRef] [Google Scholar]
  27. Huang, G., Luo, X., Wang, S., et al. (2022) Hippocampus-heuristic character recognition network for zero-shot learning in Chinese character recognition. Pattern Recognition, Vol. 130, 108818. [CrossRef] [Google Scholar]
  28. Zhou, Y.C., Tan, Q.H., Xi, C.L. (2021) Offline Handwritten Chinese Character Recognition of SqueezeNet and Dynamic Network Surgery. Journal of Chinese Computer Systems, 42(3), 556–560. [Google Scholar]
  29. Zhang, J.S., Du, J., Dai, L.R. (2020) Radical analysis network for learning hierarchies of Chinese characters. Pattern Recognition, 103: 1–13. [Google Scholar]

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