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Red Fuji apple shape data enhancement device and method

A shape data and enhancement device technology, which is applied in the field of artificial intelligence and deep learning, can solve the problems that the research cannot achieve the expected purpose, the workload is heavy, and the quality of shape data is different.

Pending Publication Date: 2021-03-26
BEIJING WUZI UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most of the apple shape data used in research studies are mostly small sample data taken by researchers themselves, and most of the shooting methods are manual shooting. This method has low work efficiency, heavy workload, irregular shooting environment, and often due to Human factors and other factors cause the quality of the obtained shape data to vary, and it is easy to cause the entire research to fail to achieve the expected purpose due to the small sample size of the data, which seriously affects the subsequent data analysis

Method used

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  • Red Fuji apple shape data enhancement device and method
  • Red Fuji apple shape data enhancement device and method
  • Red Fuji apple shape data enhancement device and method

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Embodiment 1

[0122] Before the embodiment of the present invention is described in detail, the following statement is made, Image 6 , Figure 7 , Figure 8 As a drawing for understanding the working process of the deep convolutional generation adversarial network in the image generation device 104 of the embodiment of the present invention, it contains the apple shape feature, but it is not a feature of interest to the deep convolutional generation adversarial network of the embodiment of the present invention Limitation of the scope, the features of interest of the deep convolution generation confrontation network of the embodiment of the present invention may also include but not limited to: the color, fruit shape, fruit rust, fruit surface defects of the apple in the apple photo, and the generation of confrontation by depth convolution Features identified by network algorithms that cannot be distinguished by humans;

[0123] Begin to describe the embodiment of the present invention b...

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Abstract

The embodiment of the invention provides a red Fuji apple shape data enhancement device and method, and the method comprises the steps: carrying out the photographing of an apple through a shape dataobtaining device under the control of a controller, and forming an original data set; performing classification calibration on the pictures in the original data set through a data classification device to obtain a calibration data set; dividing a region of interest for the pictures in the calibration data set through a data cutting device, cutting to eliminate noise, and reserving the region of interest to form a sample data set; and inputting the sample data set into a deep convolutional generative adversarial network through a picture generation device, performing training processing, generating a new apple picture, and forming a result data set to obtain enhanced data of the appearance of the red Fuji apple.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence and deep learning, in particular to a red Fuji apple shape data enhancement device and method. Background technique [0002] The apple industry is one of the important fruit and vegetable industries in my country. The research on the shape of apples is an important link to improve the quality of apples and promote the development of the apple industry. However, there is a lack of large-scale apple image data with good quality and complete classification when conducting related research on apples. Most of the apple shape data used in research studies are mostly small sample data taken by researchers themselves, and most of the shooting methods are manual shooting. This method has low work efficiency, heavy workload, irregular shooting environment, and often due to Human factors and other factors cause the quality of the obtained shape data to vary, and it is easy to cause the entir...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/34G06N3/04G06N3/08G06T5/00H04N5/76H04N5/235
CPCG06N3/08H04N5/76G06T2207/20032G06V20/00G06V10/25G06V10/267H04N23/74G06N3/045G06T5/70Y02P90/30
Inventor 孙立梁凯博周丽李珍萍杨玺
Owner BEIJING WUZI UNIVERSITY
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