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Image labeling method based on layer-by-layer label fusing deep network

A deep network and label fusion technology, applied in the field of social network image labeling, can solve problems such as unsatisfactory effects

Inactive Publication Date: 2014-09-03
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This type of method has achieved good results to a certain extent, but because it only uses visual information and ignores its contextual text information, its effect is still not ideal.

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  • Image labeling method based on layer-by-layer label fusing deep network
  • Image labeling method based on layer-by-layer label fusing deep network
  • Image labeling method based on layer-by-layer label fusing deep network

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Embodiment Construction

[0015] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0016] The relevant data sets involved in the method proposed by the present invention include: 1) training set, which includes images and social labels corresponding to the images; 2) test set, which only includes test images to be labeled without label information.

[0017] Considering the heterogeneity of the underlying visual information and social tag information of the image, the present invention proposes an image tagging method based on a layer-by-layer tag fusion deep network. The core idea of ​​this method is to fuse label information and visual information layer by layer under the framework of deep network, so as to learn the hierarchical features of images and provide feature representation for image annotation...

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Abstract

The invention discloses an image labeling method based on a layer-by-layer label fusing deep network. The method comprises the following steps: extracting a bottom layer vision characteristic for a training image with centralized training; layering the label of the training image to construct a hierarchical structure of the label; fusing the bottom vision characteristic information and label information layer by layer for the training image and obtaining the layered characteristic representation of the training image through parameter learning of the deep network; extracting a bottom layer vision characteristic for a testing image with centralized test, thereby obtaining the layered characteristic representation through deep network learning; and finally, forecasting the labeling information of the image according to layered characteristic representation of the testing image. The image labeling method disclosed by the invention belongs to layered labeling and is more precise than conventional labeling methods.

Description

technical field [0001] The invention relates to the technical field of social network image tagging, in particular to an image tagging method based on layer-by-layer tag fusion deep network. Background technique [0002] In recent years, with the continuous development of social media, the number of images on social platforms has exploded. How to label massive social images has become an important research content in the field of network multimedia. [0003] The current mainstream image annotation methods mainly focus on methods based on visual information. This type of method first extracts the underlying features, and then uses machine learning models to classify images based on feature representation. This type of method has achieved good results to a certain extent, but its effect is still not ideal because it only uses visual information and ignores its contextual text information. [0004] The core of image annotation is to use image-related information (including vis...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/66
CPCG06F16/58G06V30/194
Inventor 徐常胜袁召全桑基韬
Owner INST OF AUTOMATION CHINESE ACAD OF SCI