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Image retrieval method and device based on deep learning

A technology of image retrieval and deep learning, applied in the computer field, can solve the problems of low retrieval efficiency, long time-consuming, large amount of computation, etc.

Active Publication Date: 2020-07-07
CHONGQING ZHUBAJIE NETWORK
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These methods are computationally intensive and time-consuming, and the retrieval efficiency is low

Method used

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  • Image retrieval method and device based on deep learning
  • Image retrieval method and device based on deep learning
  • Image retrieval method and device based on deep learning

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Embodiment Construction

[0043] Embodiments of the technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, so they are only examples, and should not be used to limit the protection scope of the present invention.

[0044] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application shall have the usual meanings understood by those skilled in the art to which the present invention belongs.

[0045] Such as figure 1 As shown, the present embodiment provides a deep learning-based image retrieval method, including:

[0046] Step S1, inputting the image to be retrieved into the deep learning network, using the deep learning network to acquire the first image features, and obtaining the image category corresponding to the image to be retrieved.

[0047] Wherein, the fir...

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Abstract

The present invention relates to an image retrieval method and device based on deep learning. The method includes: inputting an image to be retrieved into a deep learning network, using the deep learning network to obtain first image features, and obtaining the image corresponding to the image to be retrieved. Image category; Recall image features of related images from the image feature library according to the image category; respectively calculate the first similarity probability of the first image feature of the image to be retrieved and the image feature of each recalled image; according to The recalled images are sorted by the first similarity probability, and the recalled images ranked first are returned to the user as retrieval results. The image retrieval method and device based on deep learning provided by the present invention uses the deep learning network to extract image features to calculate the similarity between images, improves the retrieval accuracy of similar images, uses the deep learning network to classify images, and reduces the number of image recalls , which improves the image retrieval efficiency.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an image retrieval method and device based on deep learning. Background technique [0002] In the past, users often searched for relevant content based on text, but with the advent of the era of big data and the rapid growth of Internet image resources, people have put forward higher requirements for image retrieval methods. How to quickly and effectively use large-scale image resources Retrieving images that users need accurately is a key problem that needs to be solved urgently, especially in the vicinity of online shopping, trademark retrieval, and appearance patent retrieval, image-based retrieval is particularly important. [0003] Taking trademarks as an example, the number of trademark applications in my country is increasing year by year. As of 2016, the number of trademark applications nationwide reached 3.52 million. The number of similar trademark inquiries is deter...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/583G06K9/62
CPCG06F16/583G06F18/22
Inventor 镝来周红伟李凯任伟李庆郭奇杰周杨刘川郁
Owner CHONGQING ZHUBAJIE NETWORK