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Handwriting numeral recognition method based on convolutional neural network and support vector machine

A convolutional neural network, support vector machine technology, applied in character and pattern recognition, computer parts, instruments, etc., can solve the problem of inability to extract expression ability, good and other problems, to ensure translation and zoom invariance, eliminate Redundant features, good recognition accuracy

Inactive Publication Date: 2016-02-10
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, this method cannot extract features with good expressive ability when the amount of handwritten digital data increases.

Method used

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  • Handwriting numeral recognition method based on convolutional neural network and support vector machine

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Embodiment Construction

[0023] Below in conjunction with accompanying drawing, the present invention will be further described:

[0024] Such as figure 1 Shown, the concrete steps of the handwritten digit recognition method of the present invention in conjunction with convolutional neural network and support vector machine are:

[0025] Step 1: Initialize all parameters in the convolutional neural network, including: the number of all convolution kernels and downsampling layers, the size of the convolution kernel, the reduction rate of downsampling, initialize the convolution kernel and bias, and so on.

[0026] Step 2: Forward propagation stage: first take a batch of samples from the sample set (X, Y P ), where X is a vector of sample numbers, Y is the expected value corresponding to X, and P is a number from 0 to 9. Input X into the network and calculate the corresponding actual output O P , O P =F n (...F 2 (F 1 (X P *W (1) )W (2) )W (n) ), n is the nth layer of the convolutional neural...

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Abstract

The present invention claims a handwriting numeral recognition method based on a convolutional neural network and a support vector machine. The method organically combines a convolutional neural network model with a support vector machine model. A handwriting numeral recognition model combining the convolutional neural network with the support vector machine can deeply describe correlation between sample data and expected data and automatically learn an image feature from original data, has very good decision plane, and is very strong in discrimination capability of digital pattern classification. The handwriting numeral recognition method based on the convolutional neural network and the support vector machine, provided by the present invention, is simple, easy to implement, and very good in handwriting numeral recognition effect.

Description

technical field [0001] The invention relates to a handwritten digit recognition method combining CNN and SVM, in particular to a handwritten digit recognition method combining convolutional neural network and support vector machine. Background technique [0002] As an important branch of image recognition applications, handwritten digit recognition is gradually showing its importance in production and life. Handwritten digit recognition can be used to read bank check information, envelope postal code information, customs and other occasions that need to process a large number of character information entry. Therefore, people's requirements for the handwritten digit recognition system established by the computer are also constantly increasing. To complete the task of recognizing Arabic numerals, the prerequisite for the handwritten digit recognition system is to build a handwritten digit recognition model, so the most basic problem in the research of handwritten digit recogni...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/2411
Inventor 唐贤伦陈龙周家林刘庆张娜周冲张毅郭飞
Owner CHONGQING UNIV OF POSTS & TELECOMM
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