Multi-layer image feature extraction modeling, image recognition method and device based on neural network
An image feature extraction and neural network technology, applied in the field of image recognition, can solve problems such as only considering face pictures, and achieve the effect of improving image recognition accuracy
Active Publication Date: 2018-04-20
GUANGZHOU SHIYUAN ELECTRONICS CO LTD
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In the training of the model in the face recognition neural network, only the identity information of the face picture is considered, and the recognition accuracy of the face recognition using this model needs to be further improved
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[0033] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the associated drawings. Preferred embodiments of the invention are shown in the accompanying drawings. However, the present invention can be embodied in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the understanding of the disclosure of the present invention more thorough and comprehensive.
[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field of the invention. The terms used herein in the description of the present invention are for the purpose of describing specific embodiments only, and are not intended to limit the present invention. As used herein, the term "or / and" includes any and all combinations of one or more of ...
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The present invention provides a neural network-based multi-layer image feature extraction modeling method and device, which can obtain the first picture, the second picture, the first classification of the first picture and the second picture of the second picture from the training set of the preset application scene. Two classifications; determine the global loss cost function value according to the first picture, the first classification, the second picture and the second classification; train the multi-layer image object verification neural network on the training set according to the global loss cost function value and training parameters; The test set of the application scene is set to test the multi-layer image object verification neural network, and the test accuracy is determined according to the test results, and the target multi-layer image object verification feature extraction model is determined according to the test accuracy and the multi-layer image object verification neural network. The method and device can achieve the beneficial effect of improving the accuracy of image recognition when the image feature model obtained by modeling is applied to an image recognition application scene for image recognition. The invention also provides an image recognition method and device.
Description
technical field [0001] The invention relates to the technical field of image recognition, in particular to a neural network-based multi-layer image feature extraction modeling method and device, and an image recognition method and device. Background technique [0002] Image recognition is a technology for computers to process, analyze and understand images to identify targets and objects in various patterns. Face recognition is face recognition, which is a biometric recognition technology based on human facial feature information. Generally, after a camera or camera collects an image or video stream containing a human face, it is automatically detected in the image. Detect and track faces in the middle, and then perform face recognition on the detected faces, which is usually also called portrait recognition and facial recognition. [0003] At present, face recognition algorithms are based on face photos and corresponding identity information, use neural networks for model ...
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IPC IPC(8): G06K9/62G06K9/46G06N3/08
CPCG06N3/08G06V10/462G06F18/24
Inventor 张玉兵
Owner GUANGZHOU SHIYUAN ELECTRONICS CO LTD