Face age estimation method based on deep learning

A deep learning, deep learning network technology, applied in neural learning methods, computing, computer components and other directions to achieve the effect of avoiding weight parameters

Inactive Publication Date: 2017-09-26
HUAQIAO UNIVERSITY
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  • Abstract
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Problems solved by technology

[0003] However, because the existing age image data sets are all small data sets, overfitting occurs in the process of app

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  • Face age estimation method based on deep learning
  • Face age estimation method based on deep learning

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Embodiment Construction

[0029] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments It is some embodiments of the present invention, but not all of them. Based on the implementation manners in the present invention, all other implementation manners obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention. Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the implementation manners in the present invention, all other implement...

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Abstract

The present invention provides a face age estimation method based on deep learning. The method comprises: S1: establishing a deep learning network model; S2: employing a classification mode to perform pre-training of the deep learning network model to allow the deep learning network model to have a classification capacity; S3: performing fine regulation on the basis of the step S2, and allowing the deep learning network model to have capabilities of learning of an appearance age and estimation of the appearance age; S4: using 80% of a data set in a real age data set as a training set to perform fine regulation of the deep learning network model, and using the 20% of the data set in the real age data set as a test set to perform the test of the deep learning network model; S5: constructing an indirect regression method to estimate an age value on the basis of the software output value of the last one full connection layer in a convolutional neural network model; and S6: inputting a detected face image, and obtaining the face age of the detected face image.

Description

technical field [0001] The present invention relates to the technical field of computer identification, in particular to a method for estimating the age of a human face based on deep learning. Background technique [0002] In recent years, with the rise of deep learning, it has been widely used in many fields, especially in the field of computer vision. Deep learning is derived from the research of artificial neural networks, and including multiple hidden layers is a structure of deep learning. Deep learning is to combine low-level features to form more abstract high-level representation category attributes or features, and to use multi-layer modeling to discover the distribution characteristics of data. Due to the structural characteristics of deep learning, it is especially suitable for the field of image processing. [0003] However, because the existing age image data sets are all small data sets, overfitting occurs in the process of applying the deep transfer learning...

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Application Information

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IPC IPC(8): G06K9/00G06N3/08
CPCG06N3/08G06V40/178G06V40/172
Inventor 杜吉祥郑德鹏范文涛张洪博翟传敏
Owner HUAQIAO UNIVERSITY
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