Towards Understanding and Improving Handwriting with AI
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-21648-0_23
Reference22 articles.
1. Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Süsstrunk, S.: SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274–2282 (2012)
2. Agius, A., et al.: Dataset of coded handwriting features for use in statistical modelling. Data Brief 16, 1010–1024 (2018)
3. Agius, A., et al.: Using handwriting to infer a writer’s country of origin for forensic intelligence purposes. Forensic Sci. Int. 282, 144–156 (2018)
4. Aksan, E., Pece, F., Hilliges, O.: DeepWriting: making digital ink editable via deep generative modeling. In: SIGCHI Conference on Human Factors in Computing Systems, CHI 2018. ACM, New York (2018)
5. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509–522 (2002)
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