Improving Handwritten Mathematical Expression Recognition via Integrating Convolutional Neural Network With Transformer and Diffusion-Based Data Augmentation
Handwritten mathematical expression recognition (HMER) poses a formidable challenge due to the intricate two-dimensional structures and diverse handwriting styles. This paper introduces a novel approach to improve HMER accuracy by employing an integrated, high-capacity architecture that combines Tra...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | Artigo |
| اللغة: | Inglês |
| منشور في: |
IEEE
2024-01-01
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| سلاسل: | IEEE Access |
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ieeexplore.ieee.org/document/10529259/ |
| الوسوم: |
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