Handwritten mathematical expression recognition based on ResNet and transformer

Lidong Lu; Lingming Cao

doi:10.1117/12.2684187

1 August 2023 Handwritten mathematical expression recognition based on ResNet and transformer

Lidong Lu, Lingming Cao

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127543B (2023) https://doi.org/10.1117/12.2684187
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

Recognition of handwritten mathematical expressions (HMER) is a branch of Optical Character Recognition (OCR). In this paper, a seq2seq model with encoder-decoder structure is constructed based on ResNet and Transformer deep neural networks, and end-to-end training is performed using open source datasets. The results of the experiments name that the character error rate of the model proposed in this paper is improved by 11.36% compared with the CNN and LSTM-based HMER model.

Citation Download Citation

Lidong Lu and Lingming Cao "Handwritten mathematical expression recognition based on ResNet and transformer", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127543B (1 August 2023); https://doi.org/10.1117/12.2684187

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