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Image recognition method and device, computer readable storage medium and processor

An image recognition and image technology, applied in the field of image processing, can solve problems such as unproposed solutions, achieve the effect of improving target detection rate, accurate recognition, and solving missed detection

Pending Publication Date: 2021-04-20
ZHUHAI GUANGTONG AUTOMOBILE +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] For the above problems, no effective solution has been proposed

Method used

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  • Image recognition method and device, computer readable storage medium and processor
  • Image recognition method and device, computer readable storage medium and processor

Examples

Experimental program
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Embodiment 1

[0025] According to an embodiment of the present invention, an embodiment of an image recognition method is provided. It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and, although A logical order is shown in the flowcharts, but in some cases the steps shown or described may be performed in an order different from that shown or described herein.

[0026] figure 1 is a flowchart of an image recognition method according to an embodiment of the present invention, such as figure 1 As shown, the image recognition method includes the following steps:

[0027] Step S102, acquiring an image to be recognized;

[0028] Step S104, the image to be recognized is input into the trained yolo-final model, and the target of the image to be recognized is identified by the yolo-final model, wherein the yolo-final model includes at least the original yolo neural network ...

Embodiment 2

[0063] According to another aspect of the embodiments of the present invention, an image recognition device is also provided, figure 2 is a schematic diagram of an image recognition device according to an embodiment of the present invention, such as figure 2 As shown, the image recognition device includes: an acquisition unit 22 and a recognition unit 24 . The image recognition device will be described in detail below.

[0064] The acquisition unit 22 is used to obtain the image to be recognized; the recognition unit 24 is connected to the above-mentioned acquisition unit 22, and is used to input the image to be recognized into the trained yolo-final model, and the target of the image to be recognized is recognized by the yolo-final model , wherein the yolo-final model at least includes the original yolo neural network model and the final layer neural network module added at the end of the original yolo neural network model, the final layer neural network module is used to ...

Embodiment 3

[0073] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, the computer-readable storage medium includes a stored program, wherein, when the program is running, the device where the computer-readable storage medium is located is controlled to execute any of the above-mentioned A method for image recognition.

[0074] Optionally, in this embodiment, the above-mentioned computer-readable storage medium may be located in any computer terminal in the computer terminal group in the computer network, and / or in any mobile terminal in the mobile terminal group, and the above-mentioned computer may The read storage medium includes stored programs.

[0075] Optionally, control the device where the computer-readable storage medium is located to perform the following functions when the program is running: acquire the image to be recognized; input the image to be recognized into the trained yolo-final model, an...

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PUM

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Abstract

The invention discloses an image recognition method and device, a computer readable storage medium and a processor. The method comprises the steps of obtaining a to-be-identified image; and inputting the to-be-identified imageto the trained yolo-final model, and enabling the yolo-final model to identify the target of the to-be-identified image, wherein the yolo-final model at least comprises an original yolo-final neural network model and a final layer neural network module added at the tail end of the original yolo-final neural network model, and the final layer neural network module is used for indicating the number of neurons and weight parameters of the identified target. According to the invention, the technical problem of missed detection of certain targets by a yolo series target detection neural network model in the prior art is solved.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image recognition method, device, computer readable storage medium and processor. Background technique [0002] In recent years, with breakthroughs in deep learning technology, the performance of object recognition and detection in camera images has been greatly improved. Therefore, in recent years, deep learning technology has been gradually applied to the target detection of autonomous driving camera perception systems. Among them, for target detection, the more classic deep learning models include: Faster RCNN and YOLO series, of which the yolo series is due to its high real-time performance. It is more widely applied to real-time detection systems like autonomous driving, and new versions such as yolo-v4 / yolo-v5 will be developed from yolo-v3 to 2020. [0003] Through the in-depth practical research on the yolo series deep learning neural network model in...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/06G06N3/08
Inventor 刘平
Owner ZHUHAI GUANGTONG AUTOMOBILE
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