Face recognition neural network training method, system and device and storage medium

Abstract

The invention discloses a face recognition neural network training method, system and device and a storage medium, and the method comprises the following steps: obtaining a face image as a training set and a test set, and combining a loss function of a face recognition neural network with an adaptive additional loss function; inputting the preprocessed training set into a face recognition neural network for training; inputting the test set into the trained face recognition neural network, and verifying the recognition accuracy of the trained face recognition neural network. According to the invention, when the face recognition neural network is trained, the loss function is combined with an adaptive additional loss function to obtain a final loss function; the intra-class distance when theface images are classified is shortened through the final loss function, the inter-class distance when the face images are classified is increased, meanwhile, balance of multi-sample classes and few-sample classes is considered, when sample distribution is unbalanced, the generalization performance of the face recognition neural network can be guaranteed, and the accuracy and reliability degree of face recognition are improved.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a face recognition neural network training method, system, equipment and storage medium. Background technique [0002] Face recognition is one of the most widely used biometric technologies in recent years. It has more and more applications in video surveillance, identity confirmation, electronic payment, criminal investigation cases and other fields. With more and more application scenarios, more and more As it becomes more complex, the speed and accuracy of face recognition become more and more important. Continuously improving the speed and accuracy of face recognition algorithms is one of the current research hotspots in the field of artificial intelligence. [0003] At present, face recognition application scenarios are becoming more and more complex, with more and more data, and people's requirements for the accuracy of face recognition algorithms are also getting higher an...

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a face recognition neural network training method, system, equipment and storage medium, which are used to solve the loss function used in the face recognition neural network in the prior art, and are only applicable to samples with the same distribution of all classes In some cases, when the sample distribution is unbalanced, the trained face recognition neural network has the technical problem of low face recognition accuracy.

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