A Convolutional Neural Network Handwriting Recognition Sorting Stability Effect Evaluation System and Method

Abstract

The invention relates to a system and method for evaluating the stability of convolutional neural network handwriting recognition and sorting effects, including a convolutional neural network handwriting recognition module, a parameter estimation module and an uncertainty calculation module. Among them, the convolutional neural network handwriting recognition module takes the user's handwritten data as input data, passes through the convolutional neural network (CNN), and finally outputs the predicted classification probability, and sorts according to this classification; the parameter estimation module uses the convolutional neural network (CNN) )'s handwriting recognition module output: take the predicted probability of the recognition module as input, and use statistical methods to estimate the parameters required for the calculation of the uncertainty of the relationship; the uncertainty calculation module takes the parameters output by the parameter estimation module as input data , by designing a fusion probabilistic calculation model of data uncertainty and data relationship uncertainty, to estimate the stability of convolutional neural network handwriting recognition ranking results.

Description

technical field [0001] The invention belongs to the field of effect evaluation, and in particular relates to a system and method for evaluating the stability of handwriting recognition and sorting by a convolutional neural network. Background technique [0002] Handwriting recognition refers to the process of informatizing the orderly trajectory generated when writing on a handwriting device into the internal code of Chinese characters. In fact, it is a mapping process from the coordinate sequence of the handwritten trajectory to the internal code of Chinese characters. It is the most natural human-computer interaction. , One of the most convenient means. With the popularization of mobile information tools such as smart phones and PDAs, handwriting recognition technology has also entered the era of large-scale application. [0003] The standard for evaluating the quality of a handwritten character is mainly determined by the accuracy of the recommended characters after reco...

AI Technical Summary

Problems solved by technology

[0004] The technical solution of the present invention is to overcome the deficiencies of the prior art, provide a convolutional neural network handwriting recognition and sorting stability evaluation system, and establish a recognition effect that can represent data uncertainty and sorting stability for convolutional neural network handwriting recognition Evaluate the model to solve the problem that the stability of identification ranking is difficult to estimate

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