Image recognition method based on convolutional neural network

A convolutional neural network and image recognition technology, applied in the field of image recognition based on convolutional neural network, can solve the problem of low image recognition rate and achieve the effect of improving the image recognition rate

Active Publication Date: 2019-12-13
瑞森网安(福建)信息科技有限公司
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Problems solved by technology

In this method, after the neural network is trained, the parameters involved in the neural network will not change, and the network will no longer change, so a single neural network model will show that some of the images have a low recognition rate.

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  • Image recognition method based on convolutional neural network
  • Image recognition method based on convolutional neural network

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[0028] In order to explain in detail the technical content, structural features, achieved goals and effects of the technical solution, the following will be described in detail in conjunction with specific embodiments and accompanying drawings.

[0029] see figure 1 As shown, it is a flowchart of an image recognition method based on a convolutional neural network, and the method includes the following steps,

[0030] S1, image segmentation, using different methods for image segmentation;

[0031] S2. Perform feature extraction on the segmented image, and use different feature extraction methods for images segmented by different segmentation methods;

[0032] S3. The extracted features are input to the same convolutional neural network model for image recognition, and multiple image recognition results are obtained;

[0033] S4. Calculate the final result of image recognition by presetting the recognition result weight corresponding to each image segmentation method:

[0034...

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Abstract

The invention belongs to the technical field of image recognition, and particularly relates to an image recognition method based on a convolutional neural network. According to the method, different segmentation methods are adopted to perform image segmentation on the same image; and for different segmentation methods, different feature extraction algorithms are adopted to extract image features,the extracted image features are inputted to the same convolutional neural network model for identification, and the final identification result of the image is calculated in combination with the identification results of different weights.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and more specifically relates to an image recognition method based on a convolutional neural network. Background technique [0002] Image recognition refers to the technology of using computers to process, analyze and understand images to identify targets and objects in various patterns. It is a practical application of deep learning algorithms. At this stage, image recognition technology is generally divided into face recognition and commodity recognition. Face recognition is mainly used in security inspection, identity verification and mobile payment; commodity recognition is mainly used in the process of commodity circulation, especially unmanned shelves, smart retail cabinets, etc. Unmanned retail area. The traditional image recognition process is divided into four steps: image acquisition→image preprocessing→feature extraction→image recognition. Image recognition performs feature...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/34G06K9/62
CPCG06V10/267G06F18/241
Inventor 林少鹏林李凤
Owner 瑞森网安(福建)信息科技有限公司
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