Multi-task deep learning network-based training method, system, multi-task deep learning network-based identification method and system

A deep learning network and multi-task technology, applied in the field of recognition methods and systems, training methods based on multi-task deep learning networks, can solve the problems of reduced overall network performance, low efficiency of training and recognition, etc.

Active Publication Date: 2017-03-15
CHONGQING ZHONGKE YUNCONG TECH CO LTD
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing single-task deep learning network is inefficient in training

Method used

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  • Multi-task deep learning network-based training method, system, multi-task deep learning network-based identification method and system
  • Multi-task deep learning network-based training method, system, multi-task deep learning network-based identification method and system
  • Multi-task deep learning network-based training method, system, multi-task deep learning network-based identification method and system

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Embodiment Construction

[0052] In the embodiment of the present invention, first obtain the human face area of ​​the human face image in the training set; perform key point detection on the human face area to obtain the key feature point position of the human face area; according to the key feature position, the The face image is subjected to affine transformation to obtain an aligned face image; the aligned face image is input to a multi-task deep learning network for training to obtain a multi-task deep learning network model; then, according to the trained multi-task deep learning network model Feature extraction and recognition of the face image to be recognized.

[0053] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0054] Embodiments of the present invention propose a training method based on a multi-task deep learning network, such as figure 1 As shown, the method includes:

[0055] Step S100: Obtain ...

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Abstract

The invention provides a multi-task deep learning network-based training method, a multi-task deep learning network-based training system, a multi-task deep learning network-based identification method and a multi-task deep learning network-based identification system. The training method includes the following steps that: the face region of a face image in a training set is obtained; key point detection is performed on the face region, so that key feature point positions are obtained; affine transformation is performed on the face image according to the key feature positions, so that an aligned face image can be obtained; and the aligned face image is inputted into a multi-task deep learning network, so that training can be carried out, and therefore, a multi-task deep learning network model can be obtained. The identification method includes the following steps that: affine transformation is performed on a face image to be identified according to the key feature positions of the face image to be identified, so that an aligned face image can be obtained; the aligned face image is inputted into a trained multi-task deep learning network model, so that feature extraction can be carried out, and feature information can be obtained; and the feature information of the face image to be identified is matched with feature information corresponding to each face image in a registration set, so that identification results can be obtained. With the methods and systems adopted, the training and identification efficiency of the multi-task deep learning network can be improved.

Description

technical field [0001] The present invention relates to the technical field of face recognition, in particular to a training method, recognition method and system based on a multi-task deep learning network. Background technique [0002] Face recognition technology is a biometric-based identification method that uses the physiological or behavioral characteristics that humans possess and can uniquely identify their identity for identity verification. With the increasing application of human-computer interaction technology, face recognition technology is of great significance in the field of human-computer interaction. As one of the main research methods in the field of pattern recognition and machine learning, a large number of face recognition algorithms have been proposed. [0003] At present, in face recognition and its various attribute recognition methods, the deep learning network is usually trained separately according to different tasks to obtain their respective de...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/08
CPCG06N3/08G06V40/164G06V40/169G06V40/172
Inventor 周曦焦宾
Owner CHONGQING ZHONGKE YUNCONG TECH CO LTD
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