首页> 外国专利> CHINESE CHARACTER MODEL TRAINING METHOD, CHINESE CHARACTER RECOGNITION METHOD, APPARATUS, DEVICE, AND MEDIUM

CHINESE CHARACTER MODEL TRAINING METHOD, CHINESE CHARACTER RECOGNITION METHOD, APPARATUS, DEVICE, AND MEDIUM

机译:中文字符模型的训练方法,中文字符识别方法,装置,设备和介质

摘要

Disclosed in the present application are a Chinese character model training method, a Chinese character recognition method, an apparatus, a device, and a medium. The Chinese character model training method comprises: acquiring a font image training sample, using a secondary Chinese character library to label a handwritten character image in the font image training sample, and dividing, according to a preset allocation rule, the font image training sample into a training set and a test set; inputting the training set into a convolutional cyclic neural network model, using a continuous time classification algorithm-based reverse propagation algorithm to update a weight and an offset in the convolutional cyclic neural network model, to acquire an initial handwritten character recognition model; and inputting the test set into the initial handwritten character recognition model, to acquire a recognition accuracy rate, and if the recognition accuracy rate is greater than a preset accuracy rate, determining that the initial handwritten character recognition model is a target handwritten character recognition model. The target handwritten character recognition model can recognize a handwritten character more accurately.
机译:本申请公开了一种汉字模型训练方法,汉字识别方法,装置,装置和介质。汉字模型训练方法包括:获取字体图像训练样本,利用辅助汉字库在字体图像训练样本中标注手写字符图像,并根据预设的分配规则,将字体图像训练样本划分为训练集和测试集;将训练集输入卷积循环神经网络模型,利用基于连续时间分类算法的逆向传播算法更新卷积循环神经网络模型的权重和偏移量,得到初始手写字符识别模型;将所述测试集输入所述初始手写字符识别模型,以获取识别准确率,如果所述识别准确率大于预设的准确率,则确定所述初始手写字符识别模型为目标手写字符识别模型。目标手写字符识别模型可以更准确地识别手写字符。

著录项

  • 公开/公告号WO2019232874A1

    专利类型

  • 公开/公告日2019-12-12

    原文格式PDF

  • 申请/专利权人 PING AN TECHNOLOGY(SHENZHEN) CO. LTD.;

    申请/专利号WO2018CN94405

  • 发明设计人 WU QI;ZHOU GANG;

    申请日2018-07-04

  • 分类号G06K9;

  • 国家 WO

  • 入库时间 2022-08-21 11:14:24

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