Face retrieving method and device based on L1 norm neural network

A neural network and L1 norm technology, applied in the field of face retrieval based on L1 norm neural network, can solve the problems of long retrieval time, low accuracy of face retrieval technology, and inability to distinguish twins, and achieve fast retrieval speed. , strong learning ability, high accuracy effect

Inactive Publication Date: 2017-10-10
GUANGDONG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0003] However, the accuracy of current face retrieval technology is generally not high, especially in the aspect of twins, there is almost no way to distinguish them, and the face retrieval technology with higher accuracy will take a long time to retrieve

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  • Face retrieving method and device based on L1 norm neural network
  • Face retrieving method and device based on L1 norm neural network
  • Face retrieving method and device based on L1 norm neural network

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Embodiment Construction

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0056] The embodiment of the invention discloses a human face retrieval method based on an L1 norm neural network, so as to improve the accuracy of human face retrieval and reduce the retrieval time.

[0057] see figure 1 , a kind of face retrieval method based on L1 norm neural network that the embodiment of the present invention provides, specifically comprises:

[0058] S101. Obtain a neural network using pore training samples and a cost function based on the L...

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Abstract

The invention discloses a face retrieving method based on an L1 norm neural network. A neural network can be obtained by means of a cost function of an L1 norm and a pore training sample, and an image matched with a test image is retrieved in a retrieval database through the neural network. Due to the fact that parameters in the neutral network obtained on the basis of the cost function of the L1 norm are determined, the phenomenon that the parameters are redefined according to different test images cannot occur for each retrieval, the retrieval speed is high, and the consumed time is less; meanwhile, the neutral network determined on the basis of the L1 norm is the neural network for deep learning, the powerful learning capacity is achieved, and test image characteristic information can be fully learned, so that the accuracy is very high. The invention further provides a face retrieving device based on the L1 norm neural network, and the technical effect can be achieved.

Description

technical field [0001] The present invention relates to the field of face recognition, and more specifically, relates to a face retrieval method and device based on an L1 norm neural network. Background technique [0002] With the development of science and technology, face retrieval technology has also been developed rapidly. Face retrieval is a technology that searches a photo uploaded by a person to find other photos of that person online. For example, if a user adds a name to a person in a photo in an album on a social networking site, the system can use face retrieval technology to automatically add the name to other photos of the same face in the same album. In addition, the technology of face retrieval is also applied to search engines to realize "searching pictures by pictures", that is, using one picture, all other pictures that are the same as the face in the picture can be retrieved. [0003] However, the accuracy of current face retrieval technology is generall...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/00G06K9/62G06N3/02
CPCG06F16/583G06N3/02G06V40/16G06V40/168G06F18/214
Inventor 范为铨李东
Owner GUANGDONG UNIV OF TECH
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