Summary of Mathwriting: a Dataset For Handwritten Mathematical Expression Recognition, by Philippe Gervais et al.
MathWriting: A Dataset For Handwritten Mathematical Expression Recognition
by Philippe Gervais, Asya Fadeeva, Andrii Maksai
First submitted to arxiv on: 16 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Human-Computer Interaction (cs.HC); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces MathWriting, the largest dataset of handwritten mathematical expressions, consisting of 230k human-written samples and an additional 400k synthetic ones. The dataset can be used for online handwriting math expression (HME) recognition, surpassing existing datasets like IM2LATEX-100K. Additionally, MathWriting can also be employed offline, making it a valuable tool for advancing research in both online and offline HME recognition. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MathWriting is a big dataset that helps computers recognize handwritten math problems. It’s really big – 630k samples! This will help make computers better at recognizing math problems written by hand, whether they’re online or offline. |
