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Method for grading stacked large-leaf crops by adopting deep learning

A technology of deep learning and crops, applied to instruments, character and pattern recognition, computer components, etc., can solve the problems of slow grading and damage to large-leaf crops, and achieve low power consumption, simple operation, and high productivity. high effect

Pending Publication Date: 2020-07-10
BEIJING FOCUSIGHT TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is to provide a method for grading stacked large-leaf crops using deep learning in order to solve the problems of slow grading speed of large-leaf crops by existing machines and damage to large-leaf crops during the grading process

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  • Method for grading stacked large-leaf crops by adopting deep learning

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Embodiment Construction

[0018] The present invention will now be described in further detail in conjunction with the accompanying drawings and preferred embodiments. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the configurations related to the present invention.

[0019] Such as figure 1 Shown is a method of grading stacked large-leaf crops using deep learning. Farmers stack the collected large-leaf crops in baskets, pots or directly on the conveyor belt, and the conveyor belt moves forward in a flat manner. Conveying, when the bundled or stacked large-leaf crops on the conveyor belt pass the camera, the camera will take the original image of the large-leaf crop. The original image is first identified by the pre-processing module. If the effective In the area of ​​large-leaf crops, the preprocessing module determines that the large-leaf crops are abnormal products, and outputs the re...

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Abstract

The invention relates to a method for grading big-leaf crops, in particular to a method for grading stacked large-leaf crops by adopting deep learning, and aims to solve the problems of low (fixed) grading (low speed) productivity and easiness in damaging the large-leaf crops of an existing (single-chip) machine. The method comprises the steps: acquiring an original image; enabling a preprocessingmodule to recognize a large-leaf crop area; if the effective large-leaf crop area is not recognized, judging that the large-leaf crop is an abnormal product; if the effective large-leaf crop area canbe recognized, transmitting the original image to the analysis and detection unit and the display image processing module at the same time; transmitting the extracted various parameters to a deep learning module; transmitting the data after deep learning to a data integration module; comparing the image with the changed resolution with the integrated data, and grading the big-leaf crops according to the comparison result. The method has the advantages of high productivity, no inorganic loss, simple operation and low power consumption.

Description

technical field [0001] The invention relates to a method for grading large-leaf crops, in particular to a method for grading stacked large-leaf crops by using deep learning. Background technique [0002] When collecting large-leaf crops, there are currently two ways to collect them, one is manual and the other is machine. When manually collecting large-leaf crops, it is necessary to identify bundled and stacked large-leaf crops, which has low efficiency, high cost and expense. At the same time, there are uncertain factors such as black-box operation in manual harvesting; the accuracy of machine harvesting is high, but its speed is far from meeting the requirements of harvesting, and at the same time, manual guidance is required to ensure that the large-leaf crops enter the machine smoothly. , specifically requires manual pre-deployment, which consumes a lot of labor and has low production capacity, and machine transmission will inevitably bring a certain percentage of machin...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V10/56G06F18/241
Inventor 方志斌王岩松和江镇黄浩
Owner BEIJING FOCUSIGHT TECH