MFH fuses high-frequency DCT features with spatial features from standard HMER encoders, improving recognition accuracy by about 1 to 2 points on CROHME 2014/2016/2019.
Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition,
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MFH: Marrying Frequency Domain with Handwritten Mathematical Expression Recognition
MFH fuses high-frequency DCT features with spatial features from standard HMER encoders, improving recognition accuracy by about 1 to 2 points on CROHME 2014/2016/2019.