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

机译:手写字符模型训练方法,手写字符识别方法,装置,设备和介质

摘要

A handwritten character model training method, a handwritten character recognition method, an apparatus, a device, and a medium. The handwritten character model training method comprises: acquiring a standard Chinese character training sample, labeling the standard Chinese character training sample and obtaining the real result of each sample, performing model training according to the real result of each sample, and using a batch gradient descent-based time-dependent reverse propagation algorithm to update network parameters of a bidirectional long short-term memory neural network, so as to acquire a standard Chinese character recognition model; acquiring and using a non-standard Chinese character training sample, to train and acquire an adjusted handwritten Chinese character recognition model; acquiring and using a Chinese character sample to be tested to obtain an erroneous character training sample; and using the erroneous character training sample to update the network parameters of the handwritten Chinese character recognition model, to acquire a target handwritten Chinese character recognition model. With the handwritten character model training method, a target handwritten Chinese character recognition model having a high handwritten character recognition rate can be obtained.
机译:手写字符模型训练方法,手写字符识别方法,设备,装置和介质。手写字符模型训练方法包括:获取标准汉字训练样本,标记标准汉字训练样本,获取每个样本的真实结果,根据每个样本的真实结果进行模型训练,并采用批量梯度下降法基于时间的反向传播算法,用于更新双向长短期记忆神经网络的网络参数,从而获得标准的汉字识别模型;获取并使用非标准汉字训练样本,以训练和获取调整后的手写汉字识别模型;获取并使用待测汉字样本得到错误的汉字训练样本;使用错误的字符训练样本更新手写汉字识别模型的网络参数,以获取目标手写汉字识别模型。利用该手写字符模型训练方法,可以获得具有较高手写字符识别率的目标手写汉字识别模型。

著录项

  • 公开/公告号WO2019232857A1

    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WO2018CN94250

  • 发明设计人 WU QI;ZHOU GANG;

    申请日2018-07-03

  • 分类号G06K9/68;

  • 国家 WO

  • 入库时间 2022-08-21 11:14:24

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