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

Advertisement image classification method based on deep convolutional neural network model

A neural network model and convolutional neural network technology, applied in biological neural network models, still image data clustering/classification, image analysis, etc., can solve problems such as high resource consumption, many parameters, and long training period

Inactive Publication Date: 2019-10-15
福建省趋普物联科技有限公司
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing convolutional neural network has many parameters, the training period is long, and it consumes a lot of resources.

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
  • Advertisement image classification method based on deep convolutional neural network model
  • Advertisement image classification method based on deep convolutional neural network model
  • Advertisement image classification method based on deep convolutional neural network model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] In order to describe the technical content, structural features, achieved purpose and effect of the technical solution in detail, the following will be described in detail in conjunction with specific embodiments and accompanying drawings.

[0029] see figure 2 As shown, a preferred embodiment of the present invention is a method for classifying advertisement images based on a deep convolutional neural network model, comprising the following steps:

[0030] Step S1, image preprocessing, using grayscale stretching to achieve image enhancement, and then using median filter to filter and eliminate noise for the enhanced image.

[0031] Grayscale stretching is to achieve the purpose of enhancing the contrast by stretching the contrast.

[0032] The formula is:

[0033]

[0034] Among them, f(x, y) is the input image, F(x, y) is the output image, and the grayscale stretching can improve the image quality and make the image display effect clearer. Selectively highlight...

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 belongs to the technical field of image processing and recognition, and particularly relates to an advertisement image classification method based on a deep convolutional neural networkmodel. The method comprises the following steps: S1, preprocessing an image, realizing image enhancement by adopting gray stretching, and eliminating noise of the enhanced image by adopting filtering;and S2, inputting the preprocessed image into a convolutional neural network model for classification to obtain a classification result.

Description

technical field [0001] The invention belongs to the technical field of image processing and recognition, and more specifically, relates to a method for classifying advertising images based on a deep convolutional neural network model. Background technique [0002] In 2015, the scale of my country's outdoor electronic screen advertising market was about 11.65 billion yuan, a year-on-year increase of 15% from 10.13 billion yuan in 2014. In 2016, the scale of my country's outdoor electronic screen advertising market reached 13.102 billion yuan. In 2017, the scale of my country's outdoor electronic screen advertising market reached 14.41 billion yuan. Such as figure 1 As shown, it is a schematic diagram of the scale development of my country's outdoor electronic screen advertising market in recent years. [0003] With the continuous development of electronic screens in public places (hereinafter referred to as advertising screens) technology and the large-scale popularization o...

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): G06F16/55G06N3/04G06T5/00
CPCG06F16/55G06T2207/20032G06T2207/20081G06T2207/20084G06N3/045G06T5/70
Inventor 邹培利
Owner 福建省趋普物联科技有限公司
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