Practical Solutions and Value
Recognizing handwritten mathematical expressions (ME) has been a challenge, but Google Research’s MathWriting dataset offers practical solutions and value.
Practical Solutions:
– MathWriting dataset includes 230k human-written and 400k synthetic samples, facilitating online and offline ME recognition.
– Shared in InkML format, it expands offline HME datasets by effectively rasterizing inks, making it easier for recognition models to understand.
Value:
– MathWriting sets a new benchmark for ME recognition, featuring normalized ground truth expressions for simplified training and robust evaluation.
– With nearly 3.9 times more samples and 4.5 times more distinct labels after normalization, MathWriting covers a broader array of tokens, enabling representation of diverse scientific fields like quantum mechanics and linear algebra.
Conclusion:
– MathWriting empowers recognition research, offering extensive data and avenues for advancement across scientific domains.
– Integration with datasets like CROHME23 promises enhanced model performance and diversity.
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