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Multi-flower quality grading method based on machine learning

A quality classification and machine learning technology, applied in the field of artificial intelligence, to achieve the effect of improving classification efficiency and accuracy

Pending Publication Date: 2022-07-29
GUANGDONG VOCATIONAL & TECHNICAL COLLEGE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a multi-flower quality grading method based on machine learning, to solve one or more technical problems in the prior art, at least provide a beneficial selection or create conditions

Method used

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  • Multi-flower quality grading method based on machine learning
  • Multi-flower quality grading method based on machine learning
  • Multi-flower quality grading method based on machine learning

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Embodiment Construction

[0047] In order to make the objectives, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

[0048]It should be noted that although the functional modules are divided in the schematic diagram of the system and the logical sequence is shown in the flowchart, in some cases, the modules can be divided differently from the system, or executed in the order in the flowchart. steps shown or described. The terms "first", "second" and the like in the description and claims and the above drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0049] refer to Figure 1 to Figure 5 , a multi-flower quality grading ...

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Abstract

The invention discloses a multi-flower quality grading method based on machine learning, and the method comprises the steps: an image collection module collects an original top view image of a flower cluster, carries out the preprocessing of a preprocessing module, and obtains a first image, and a flower classification module carries out the flower classification and segmentation of the first image through a deep learning algorithm, obtaining a plurality of segmented second images and flower classification results; the processor module grays the second images to obtain gray values of the second images, the gray values serve as feature values of the second images, the flower grading module carries out quality grading on each second image through a K-means algorithm according to quality grading standards, and the quality grading standards are low quality, medium quality and high quality. And thus, a more accurate quality grading result of the flower clusters is obtained. According to the flower cluster quality grading method, quality grading can be carried out on multiple flowers in the flower cluster, the flower cluster quality grading accuracy is greatly improved, and the flower grading efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, and in particular relates to a multi-flower quality classification method based on machine learning. Background technique [0002] Flowers are herbs with ornamental value, and are a general term for fabrics used to describe appreciation. They are usually sun-loving and cold-resistant, and short branches with reproductive functions. Flower farmers or producers usually cultivate flowers belonging to the same variety together to form a flower cluster, and in the process of flower cultivation, they regularly check whether the growth of the flowers meets the quality standards. Judging the quality of flowers, this method of achieving quality grading through visual inspection is extremely inefficient, and the obtained flower quality grading results have large errors and low accuracy. Therefore, there are certain difficulties in quality classification of flowers during floriculture. SU...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V10/764G06V10/762G06V10/80G06V10/82G06V10/25G06K9/62G06N20/00
CPCG06V10/764G06V10/762G06V10/80G06V10/82G06V10/25G06N20/00G06F18/23213G06F18/2415G06F18/214G06V10/98G06V20/188G06N3/09
Inventor 刘静张久雷
Owner GUANGDONG VOCATIONAL & TECHNICAL COLLEGE