Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Food detection method and device based on neural network model

A neural network model, food detection technology, applied in the field of food detection based on neural network model, can solve the problems of poor convenience, inconvenience, large size, etc., to achieve convenient and more accurate detection, improve detection effect, reduce the effect of occupancy

Pending Publication Date: 2022-07-12
中检溯源江苏技术服务有限公司
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Traditional food quality testing methods require special testing equipment for testing. These equipment are relatively large in size and not easy to carry. It is often necessary to take relevant food samples to a special place for testing, and the convenience of testing is poor.

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 detection method and device based on neural network model
  • Food detection method and device based on neural network model
  • Food detection method and device based on neural network model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0047] Since the embodiments of the present application involve a large number of neural network applications, for ease of understanding, the related terms and concepts of the neural networks that may be involved in the embodiments of the present application are first introduced below.

[0048] (1) Neural network

[0049]Artificial Neural Networks (ANNs), also referred to as Neural Networks (NNs) or Connection Models, is an algorithmic mathematical model that...

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 provides a food detection method and device based on a neural network model, and relates to the field of artificial intelligence. The method comprises the following steps: acquiring a target image of a to-be-detected fresh food; performing convolution processing on the target image to obtain global features and local features of the target image; splicing the global features and the local features of the target image to obtain target image features of the target image; inputting the target image features into a target food quality detection model for processing to obtain first initial quality information of the fresh food; query request information is sent to a cloud management system to obtain second initial quality information of the to-be-detected fresh food, and the second initial quality information comprises a food producing area and a quality risk of the to-be-detected fresh food; and generating final quality information of the to-be-detected fresh food according to the first initial quality information and the second initial quality information.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and more particularly, to a method and apparatus for food detection based on a neural network model. Background technique [0002] With the development of the economy and the improvement of living standards, people's requirements for food materials are getting higher and higher, especially fresh food. Such products are not easy to store and have a short shelf life. discomfort. In addition, various safety incidents occur frequently in the food field. When purchasing fresh food, we often encounter quality risks such as mildew or chemical treatments such as waxing or sulfur smoking, which are lingering in the minds of consumers. shadow. [0003] Traditional food quality testing methods require special testing equipment for testing. These equipments are relatively bulky and inconvenient to carry. They often need to take relevant food samples to a special place for testin...

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): G06T7/00G06N3/04G06N3/08G06Q10/06G06Q50/26
CPCG06T7/0004G06N3/08G06Q10/06395G06Q50/26G06T2207/20081G06T2207/20084G06T2207/30128G06N3/045
Inventor 刘向阳沈爱芳汤秀秀陈靖章怀婷郁腾赵宇秋顾晓清范锦曾正宏
Owner 中检溯源江苏技术服务有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com