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Embedded Large–Scale Handwritten Chinese Character Recognition

Citation Author(s):
Hans J. G. A. Dolfing, Ryan S. Dixon, Jerome R. Bellegarda
Submitted by:
Youssouf Chherawala
Last updated:
16 May 2020 - 11:46am
Document Type:
Presentation Slides
Document Year:
Presenters Name:
Youssouf Chherawala



As handwriting input becomes more prevalent, the large symbol inventory required to support Chinese handwriting recognition poses unique challenges. This paper describes how the Apple deep learning recognition system can accurately handle up to 30,000 Chinese characters while running in real-time across a range of mobile devices.

To achieve acceptable accuracy, we paid particular attention to data collection conditions, representativeness of writing styles, and training regimen. We found that, with proper care, even larger inventories are within reach. Our experiments show that accuracy only degrades slowly as the inventory increases, as long as we use training data of sufficient quality and in sufficient quantity.

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Dataset Files

_Embedded Large Scale Handwritten Chinese Character.pdf