Digital identification method, digital identification device, neural network training method and neural network training device

Abstract

The invention discloses a digital identification method, a digital identification device, a neural network training method and a neural network training device. The digital identification method comprises the steps of acquiring a digital image sample to be identified, and identifying a digital category corresponding to the digital image sample to be identified through a neural network after training. The neural network after training is trained by the steps as follows: acquiring digital detection samples; detecting a preset neural network by using the digital detection samples, wherein the preset neural network is a neural network trained by digital training samples; judging whether the accuracy rate of the detection results reaches a preset threshold; and when judging that the accuracy rate of the detection results does not reach the preset threshold, adjusting the number of nodes output by the preset neural network, and using an error sample in the digital detection samples to retrain the preset neural network to obtain the neural network after training. The technical problem in the prior art that the precision of digital identification is low is solved.

Description

technical field [0001] The invention relates to the field of digital recognition, in particular to a digital recognition method and device, and a neural network training method and device. Background technique [0002] Electronic examination paper marking is one of the evolution trends of today's paper marking forms. The use of computers and other tools can improve the automation of the marking process, thereby achieving the purpose of increasing the speed of marking papers and reducing human consumption. In the daily teaching practice of primary and secondary schools, paper is still the main medium of test papers. How to combine the paper test paper marking process with computer technology is a topic of concern to many researchers. Especially for the subjective part, scores in numerical form are required, not purely right or wrong. The existing technology usually adopts the human-computer interaction method, that is, the examiner inputs the score to be given on the compute...

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a digital recognition method and device and a neural network training method and device to at least solve the technical problem of low digital recognition accuracy in the prior art

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