China Unionpay Co., Ltd.

Jialiang Kang

Xi Shen

Jien Zhou

Naigeng Ji

Kai Bian

Kunpeng Wang

Zhixiong Tang

Ji'en Zhou

Peilin Chai

Jingjing Gao

Jiawei Lai

Yixin Dou

Weipeng Wang

Siyuan Tang

Embodiments of the disclosure provide a recognition method, apparatus, device, and storage medium and relates to the field of artificial intelligence technology. The method includes obtaining a second decision-making threshold of a feature-matching model in a target scenario by joint testing of the feature-matching model and auxiliary detection model. The method takes into full consideration the mutual influence between different algorithm models in a scenario when multiple algorithm models are used for facial recognition. Compared to manually setting a decision-making threshold for each algorithm model independently, the methods in the disclosure are more adaptable to changing scenarios and scenarios with multiple models used in facial recognition. This improves the accuracy and efficiency of the obtained decision-making thresholds, thereby enhancing the accuracy of multi-model facial recognition.

Facial recognition method and apparatus, device and storage medium

The present application discloses a method, an apparatus, and a device for updating a feature vector database, and a medium. The method includes: acquiring a first biological feature in a service request; obtaining, according to the first biological feature, a first feature vector and a second feature vector respectively through a first algorithm model and a second algorithm model, in which a first feature vector database include sample feature vectors obtained based on the first algorithm model; performing validity verification on the second feature vector according to an associated feature vector for a first user corresponding to a first sample feature vector; and obtaining, under a condition that the validity verification on the second feature vector passes, a second sample feature vector for the first user based on the second feature vector, and storing the second sample feature vector in a second feature vector database.

Method, apparatus and device for updating feature vector database, and medium

The application provides an image acquisition apparatus, a server, and encryption and decryption methods, and relates to the field of data processing. The image acquisition apparatus includes: an image acquisition device including an encryption processor and a data interface provided in the image acquisition device, wherein the encryption processor is configured to encrypt, by using a stored first key, image data acquired by the image acquisition device to obtain image ciphertext data; the data interface is configured to obtain the image ciphertext data and output the image ciphertext data to a terminal device. With the technical solution of the application, security of the image data can be ensured.

Image acquisition apparatus, server, and encryption and decryption methods

The application provides a data security processing terminal, system and method, and is related to a field of data processing. The data security processing terminal includes: an image acquisition device configured to acquire image data and transmit the image data to a Trust Execution Environment through a secure channel; an image acquisition driver operating in the Trust Execution Environment and configured to drive, in response to a drive instruction from a processor, the image acquisition device to acquire the image data; the processor operating in the Trust Execution Environment and configured to send the drive instruction to the image acquisition driver, obtain the image data, encrypt the image data using a stored first key to obtain image ciphertext data, and output the image ciphertext data. The technical solution of the present applicant can be used to ensure the security of image data.

Data security processing terminal and system

The present application relates to the field of data processing, and provides a method for deploying a face sample library, and a method and an apparatus for business processing based on face recognition. The method for deploying a face sample library, comprises: obtaining historical business information of users corresponding to face samples in a password face sample library under a condition that a number of face samples in the password face sample library is greater than or equal to a preset sample number threshold, wherein confidential business passwords of the users corresponding to the face samples in the same password face sample library are the same; dividing the password face sample library to obtain M levels of face sample sub-libraries according to the historical business information, where M is a positive integer. Use of the technical solution of the present application improves the accuracy of business processing using face recognition.

Method for deploying a face sample library and method and apparatus for business processing based on face recognition

The present disclosure provides an identity recognition system for a terminal. The system includes: an obtaining device configured to obtain pre-stored biometric information corresponding to a user within a preset range of the terminal; a biometric library configured to maintain the obtained pre-stored biometric information; a collection device configured to collect first biometric information of the user; and a recognition device configured to recognize the first biometric information in the biometric library, and decide to enable or disable one or more functions or components of the terminal according to a recognition result. The present disclosure further provides an identity recognition method, a computer storage medium and a terminal.

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Shanghai, China

Jialiang Kang