[1] [1] Hong Z, You N, Tan J, et al. Residual BiRNN Based Seq2Seq Model with Transition Probability Matrix for Online Handwritten Mathematical Expression Recognition[C]//2019 International Conference on Document Analysis and Recognition (ICDAR). 2019.

[3] [3] N. Pang, C. Yang, X. Zhu, J. Li and X. - C. Yin, Global Context-Based Network with Transformer for Image to Latex[C]//2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, 2021: 4650-4656.

[9] [9] Wu J W, Yin F, Zhang Y M, et al. Handwritten mathematical expression recognition via paired adversarial learning[J]. International Journal of Computer Vision, 2020, 128: 2386-2401.

[10] [10] Zhang Z, Wang T, Song X, et al. The Design and Implementation of the Natural Handwriting Mathematical Formula Recognition System[C]//Proceedings of the 6th International Conference on Advances in Image Processing. 2022: 114-121.

[11] [11] Cao Y, Xie Z, Li L. Research on Identification of Handwritten Mathematical Formulas[C]//International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019: Applications and Techniques in Cyber Intelligence. Springer International Publishing, 2020: 1494-1500.

[12] [12] Messina R, Louradour J. Segmentation - free handwritten Chinese text recognition with LSTM-RNN[C]//International Conference on Document Analysis & Recognition. IEEE, 2015.