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Fast Multi-language LSTM-based Online Handwriting Recognition
[article]
2020
arXiv
pre-print
We describe an online handwriting system that is able to support 102 languages using a deep neural network architecture. This new system has completely replaced our previous Segment-and-Decode-based system and reduced the error rate by 20%-40% relative for most languages. Further, we report new state-of-the-art results on IAM-OnDB for both the open and closed dataset setting. The system combines methods from sequence recognition with a new input encoding using B\'ezier curves. This leads to up
arXiv:1902.10525v2
fatcat:xjp56djpzbfezf63lgqoxnzsvq