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

Garbage type recognition system based on deep learning

A deep learning and identification system technology, applied in the field of computer-aided automatic identification of garbage types, can solve problems such as difficulty in effective identification and on-demand classification, and achieve the effect of increasing accuracy and robustness

Inactive Publication Date: 2019-08-13
王胜春
View PDF8 Cites 24 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, it is difficult for traditional artificial feature engineering techniques to effectively identify and customize classification on demand.

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
  • Garbage type recognition system based on deep learning
  • Garbage type recognition system based on deep learning
  • Garbage type recognition system based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0019] A garbage type identification system based on deep learning proposed in an embodiment of the present invention includes a garbage classification data set, a garbage classifier, a garbage classifier training module and a real-time garbage type identification module.

[0020] The garbage sorting data set in the embodiment of the present invention is divided into garbage types according to the "Guidelines for Sorting Domestic Garbage of Capital Citizens" issued by the official website of the Beijing City Management Committee, and there are 3 major categories and 52 subcategories in total. In addition to this, "no garbage" is also set as the fourth category, which is divided into five subcategories. About 79,000 photos were collected from the Internet, about 8,000 photos were taken manually, and a total of about 87,000 photos were used as a garbage classification data set. The structure is as follows, where KW stands for kitchen waste, OW stands for other waste, and RW stand...

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 garbage type recognition system based on a deep learning method in the field of computer-aided garbage classification. The system comprises a garbage classification data set,a garbage classifier, a garbage classifier training module and a real-time garbage type recognition module. The garbage classifier training module utilizes a garbage classification data set to traina garbage classifier, and the real-time garbage type recognition module collects image information from a camera of the real-time garbage type recognition module and then calls the garbage classifierto recognize the garbage type in an image and outputs a recognition result and a control signal. The system has the advantages that garbage classification does not depend on human garbage classification knowledge any more, and therefore the process of implementing garbage classification in China can be greatly accelerated.

Description

technical field [0001] The invention relates to a computer-aided garbage type automatic identification technology, in particular to a garbage type identification system based on a deep learning method. Background technique [0002] With the rapid development of my country's economy and the improvement of people's living standards, the amount of domestic waste has also increased sharply. According to statistics from the China Urban Environmental Sanitation Association, the annual output of urban domestic waste in the country exceeds 150 million tons, and it increases at an annual rate of 8% to 10%. About 800,000 mu. Among the 688 cities across the country, 2 / 3 of the large and medium-sized cities have been surrounded by garbage except the county seat, and 1 / 4 of the cities have no suitable places to pile up garbage. my country has become the most serious city surrounded by garbage in the world. one of the countries. Recycling of urban waste in foreign countries has entered ...

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
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/52G06F18/24G06F18/214
Inventor 王胜春
Owner 王胜春
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