Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences. In this paper, we exploit the outstanding capability of path signature to translate online pen-tip trajectories into i...

Полное описание

Библиографические подробности
Главные авторы:	Xie, Z, Sun, Z, Jin, L, Ni, H, Lyons, T
Формат:	Journal article
Опубликовано:	Institute of Electrical and Electronics Engineers 2017

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