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Image Recognition Method Based on Convolutional Neural Network Model

A convolutional neural network and image recognition technology, applied in the field of image recognition based on the convolutional neural network model, can solve the problems of power consumption, large memory overhead, time consumption, etc.

Active Publication Date: 2021-08-20
深圳市一心视觉科技有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, when running the convolutional neural network model, each binary large object (blob) of each convolutional layer corresponds to occupying a memory block, and there may even be cases where some of the memory blocks occupied by the blob are idle. For smart door locks with limited chip memory, it will cause a lot of memory overhead, and it will also cause problems such as time consumption and power consumption.

Method used

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  • Image Recognition Method Based on Convolutional Neural Network Model
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  • Image Recognition Method Based on Convolutional Neural Network Model

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Embodiment Construction

[0065] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

[0066] It should be understood that the "plurality" mentioned in this application means two or more. In the description of this application, unless otherwise specified, " / " means or means, for example, A / B can mean A or B; "and / or" in this article is just a description of the relationship between associated objects, It means that there can be three kinds of relationships, for example, A and / or B, which can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in order to clearly describe the technical solution of the present application, words such as "first" and "second" are used to distinguish the same or similar items with basically the same function and effect. Those skilled in the art can understand that words such as "first" and "second" do not limit the number ...

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Abstract

The present application provides an image recognition method based on a convolutional neural network model. The method includes: before running the i-th convolutional layer in the N convolutional layers of the first convolutional neural network model, determining the i-th memory size occupied by the blob of the i-th convolutional layer; in the memory block multiplexing pool Determine the i-th memory reuse block that is greater than or equal to the size of the i-th memory. This application adjusts the memory occupied by the operation of the convolutional neural network model, which helps to reduce the operating memory overhead of the convolutional neural network model and meets the requirements of the smart door lock scenario.

Description

technical field [0001] The present application relates to the field of electronic technology, in particular to an image recognition method based on a convolutional neural network model in the field of electronic technology. Background technique [0002] In the field of image recognition technology, it is mainly recognized through various trained convolutional neural network models. Image recognition technology is widely used in daily life. For example, in the field of smart door locks, it is mainly recognized through various trained convolutional neural network models. Realize the image recognition function of the smart door lock. At present, when running the convolutional neural network model, each binary large object (blob) of each convolutional layer corresponds to occupying a memory block, and there may even be cases where some of the memory blocks occupied by the blob are idle. For smart door locks with limited chip memory, it will cause a lot of memory overhead, and i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/62
CPCG06N3/04G06N3/08G06F18/241
Inventor 朱渊童志军丁小羽
Owner 深圳市一心视觉科技有限公司