Multi-Feature Learning by Joint Training for Handwritten Formula Symbol Recognition
Given the similarity of handwritten formula symbols and various handwriting styles, this paper proposes a squeeze-extracted multi-feature convolution neural network (SE-MCNN) to improve the recognition rate of handwritten formula symbols. The system proposed in this paper integrates the eight-direct...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9027943/ |