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

Method for analyzing food nutritional ingredients in image based on machine learning

A technology of machine learning and nutritional components, which is applied in the field of food nutritional components in images based on machine learning, can solve problems affecting nutrition and increase the difficulty of judging food category names, and achieve the effect of ensuring accuracy

Inactive Publication Date: 2021-01-22
TIANJIN UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Most of the current nutritional analysis apps need to manually input the types of food they eat, and some foods have different names in different regions, which increases the difficulty for people to judge the names of the types of food they eat, thus affecting People's judgments about their nutritional intake

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
  • Method for analyzing food nutritional ingredients in image based on machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] Embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0020] A method for analyzing food nutritional components in an image based on machine learning of the present invention specifically comprises the following steps:

[0021] Step 1. The user uploads food pictures through the self-developed APP, and the APP background obtains the food picture information uploaded by the user to the server;

[0022] Step 2. On the server, use the pre-trained model of the ResNet50 network to train the food classification model by means of transfer learning, and then input the obtained image data into the pre-trained food classification model, and use the food classification model to identify the pictures and analyze them. What kind of food is in the picture;

[0023] Step 3. The model will classify and judge the input picture, judge what kind of food it is, give the probability of this possibility, send the type ...

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 method for analyzing food nutritional ingredients in an image based on machine learning. The method comprises the following steps: step 1, acquiring food picture informationuploaded to a server by a user; 2, inputting the obtained picture data into a pre-trained food classification model, and discriminating pictures by the food classification model; 3, sending a result output by the food classification model to a mobile phone APP of the user, and the user confirms whether the food is the kind of food or not; step 4, if the food is the kind of food, enabling the userto confirm and input the weight data of the food; 5, if the type of the food is not the type of the food, enabling the user to manually input the type of the food and inputs the weight data of the food, and learning the type manually input by the user and the picture uploaded by the user again; and step 6, finally presenting a result to the user. Compared with the prior art, the picture recognition network used in the invention is specially trained by using the food data set, and has high accuracy for food picture recognition.

Description

technical field [0001] The invention relates to the technical fields of intelligent data analysis, machine learning, image analysis, etc., in particular to a method for food nutritional components in images based on machine learning. Background technique [0002] Balanced nutrition is the pursuit of quality of life for people in modern society. The energy needed for people's work and life comes from food. A reasonable diet can help meet the daily needs of people's bodies for different types of nutrients, maintain their own health, and reduce the incidence of various diseases, especially chronic diseases. However, everyday people have only a vague concept of the types and amounts of nutrients contained in food. The intake of various nutrients will directly affect our physical condition. It is an inevitable requirement to clarify the amount of nutrients in food. [0003] Most of the current nutritional analysis apps need to manually input the types of food they eat, and some...

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): G06K9/62G06F16/53G06N20/00
CPCG06F16/53G06N20/00G06F18/241G06F18/214
Inventor 刘昱刘宇航
Owner TIANJIN UNIV
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