Food-borne pathogenic bacterium classification method

A food-borne pathogenic bacteria and classification method technology, applied in the direction of instruments, biological neural network models, calculations, etc., can solve the problems of ineffective operation, cumbersome operation, high cost, etc., and achieve high accuracy and few network parameters , the effect of alleviating the problem of misjudgment

Pending Publication Date: 2019-09-17
SHANGHAI INST OF TECH
View PDF2 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The invention provides a method for classifying food-borne pathogenic bacteria, which can solve the problems of cumbersome operation, long cycle, ineffective monitoring and prevention, and high cost of the existing method

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Food-borne pathogenic bacterium classification method
  • Food-borne pathogenic bacterium classification method
  • Food-borne pathogenic bacterium classification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0025] figure 1 For the convolutional neural network classification method adopted in the present invention, such as figure 1 As shown, the method in this embodiment includes:

[0026] S1. Spectral preprocessing: use the Savitzky-Golay filter and asymmetric least squares in the Origin software to analyze the original E. coli O 157 :H 7 , Brucella S2 strain pathogen spectrum pretreatment to remove the fluorescence background, to obtain the spectrum of pathogenic bacteria;

[0027] S2. Generating a ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a food-borne pathogenic bacterium classification method. The method comprises the steps of constructing a convolutional neural network and carrying out k-fold cross validation for model evaluation. The method based on the convolutional neural network is used, and the accuracy of food-borne pathogenic bacterium spectral classification is improved through structural configuration and optimization of the convolutional neural network. The technical problem mainly solved by the invention is to realize automation of spectral data classification of the food-borne pathogenic bacteria by modeling the convolutional neural network, provide reference for food safety practitioners and improve the food safety detection efficiency.

Description

technical field [0001] The invention relates to the fields of Raman spectroscopy, food-borne pathogenic bacteria, convolutional neural network and machine learning. Background technique [0002] So far, the most commonly used method for the detection of pathogenic bacteria in food in my country is the traditional detection method of microorganisms established in accordance with the theory of biochemistry and microbiology. The most important identification methods are biochemical identification, visual morphology observation, microbial isolation and culture, and serological typing. [0003] These methods are cumbersome to operate and have a long cycle, and cannot effectively monitor and prevent them. Such as multiplex PCR detection system, FTA filter-based gene chip detection and other technologies, the classification accuracy is not high, and the number of identified species is also small. Moreover, compared with traditional machine learning algorithms, the cost of manuall...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00G06N3/04
CPCG06V20/695G06V20/698G06N3/045G06F18/241G06F18/214
Inventor 吴承炜夏钒曾曾万聃夏志平史如晋曲晗李乾学
Owner SHANGHAI INST OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap