Browse State-of-the-Art › Offline Handwritten Chinese Character Recognition
Offline Handwritten Chinese Character Recognition
2 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
Handwritten Chinese characters recognition is the task of detecting and interpreting the components of Chinese characters (i.e. radicals and two-dimensional structures).
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
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Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
2 shown of 2 papers with code (8 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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30 Dec 2018 1 repository listedRecent researches introduced fast, compact and efficient convolutional neural networks (CNNs) for offline handwritten Chinese character recognition (HCCR).
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19 May 2015 1 repository listedWe design a streamlined version of GoogLeNet [13], which was original proposed for image classification in recent years with very deep architecture, for HCCR (denoted as HCCR-GoogLeNet).
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