Handwriting model training method, handwriting recognition method, device, apparatus and medium

Abstract

The invention discloses a handwriting model training method, a handwriting character recognition method, a device, an apparatus and a medium. The handwriting model training method comprises the following steps of: obtaining a standard Chinese character training sample, and batching the standard Chinese character training sample according to a preset batch; initializing convolution neural network;convolution neural network being used to train batched Chinese character training samples, and back propagation algorithm being used to update the weight and bias of convolutional neural network, so as to obtain Chinese character recognition model; obtaining and using non-standard Chinese character training samples, training to obtain the adjusted Chinese handwritten character recognition model; aChinese character sample to be teste being obtained and adopted to obtain an error character training sample; based on the backpropagation algorithm of batch gradient descent, the weight and bias ofthe Chinese handwritten character recognition model being updated by using the error training samples, and the target Chinese handwritten character recognition model being obtained. A target Chinese handwritten character recognition model with high recognition rate can be obtained by using the handwritten model train method.

Description

technical field [0001] The invention relates to the field of Chinese character recognition, in particular to a handwriting model training method, a handwriting recognition method, a device, equipment and a medium. Background technique [0002] Traditional handwritten character recognition methods mostly include steps such as binarization processing, character segmentation, feature extraction, and support vector machine for recognition. When traditional handwritten character recognition methods are used to recognize rough non-standard characters (handwritten Chinese characters), the accuracy of recognition is high. The accuracy is not high, making its recognition effect unsatisfactory. Traditional handwritten character recognition methods can only recognize standard characters to a large extent, and the accuracy rate is low when recognizing various handwritten characters in real life. Contents of the invention [0003] Embodiments of the present invention provide a handwri...

AI Technical Summary

Problems solved by technology

[0003] The embodiment of the present invention provides a handwriting model training method, device, equipment and medium to solve the current problem of low handwriting recognition accuracy

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