Red meat classification method and device based on deep learning, equipment and storage medium

A technology of deep learning and classification methods, applied in the field of remote sensing, can solve the problem of low recognition accuracy

Inactive Publication Date: 2019-08-23
WUHAN POLYTECHNIC UNIVERSITY
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to propose a red meat classification method, device, equipment and storage med

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  • Red meat classification method and device based on deep learning, equipment and storage medium
  • Red meat classification method and device based on deep learning, equipment and storage medium
  • Red meat classification method and device based on deep learning, equipment and storage medium

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Embodiment Construction

[0065] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0066] refer to figure 1 , figure 1 It is a schematic diagram of the structure of the deep learning-based red meat classification device of the hardware operating environment involved in the solution of the embodiment of the present invention.

[0067] Such as figure 1 As shown, the red meat classification device based on deep learning may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein, the communication bus 1002 is used to realize connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a button, and the optional user interface 1003 may also include a standard wired interface and a w...

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Abstract

The invention discloses a red meat classification method and device based on deep learning, equipment and a storage medium. The method comprises the steps of obtaining to-be-classified red meat hyperspectral image information; inputting the to-be-classified red meat hyperspectral image information into a preset metric function to obtain similarity information among feature information in the to-be-classified red meat hyperspectral image information; extracting reference feature information in the to-be-classified red meat hyperspectral image information according to the similarity information;performing dimensionality reduction on the reference feature information to obtain target feature information; and performing spatial-spectral joint classification on the target feature information based on deep learning to obtain target type information, thereby firstly extracting feature information of the red meat hyperspectral image information through an appropriate preset metric function, and then extracting the spatial-spectral joint feature information based on deep learning to improve the classification precision of the red meat hyperspectral image.

Description

technical field [0001] The present invention relates to the field of remote sensing technology, in particular to a red meat classification method, device, equipment and storage medium based on deep learning. Background technique [0002] Hyperspectral technology developed in the field of remote sensing in the past decade has been applied to non-destructive testing in many fields. Compared with other images, hyperspectral images contain rich spectral information in addition to spatial information. Combining spectral processing methods and image processing The algorithm is suitable for non-destructive testing of red meat quality. At present, some achievements have been made in the detection of beef, mutton and pork based on hyperspectral technology, including tenderness, pH value, water strength, marbling and microbial chemistry; [0003] However, hyperspectral images have the characteristics of high dimensionality, spectral similarity and mixed pixels, and the amount of data...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/048G06N3/044G06N3/045G06F18/22G06F18/2135G06F18/24
Inventor 李雅琴余乾慧袁操曾山
Owner WUHAN POLYTECHNIC UNIVERSITY
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