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Social Security Face Social Security, Live Testing API
Social Security Face Social Security, Live Testing API
Social Security Face Social Security, Live Testing API
Social Security Face Social Security, Live Testing API Product Background
With the application of the deep learning method, the recognition rate of social security face social security technology has been qualitatively improved. At present, the social security rate of social security has reached more than 99%. Compared with other biometrics technology, social security social security technology has its own unique advantages in practical applications: it can be directly accessed by the camera, and the identification process can be completed in a non-contact manner, which is convenient and quick. At present, our social security face social security technology has been applied in the fields of finance, education, scenic spots, travel, and social security.
Social Security Face Social Security, Live Testing API Product Profile
Social security face social security technology is mainly divided into two parts:
The first step is the front-end human face detection API, which mainly supports the android and ios platforms. At the front end, through the combination of blinking, opening, shaking, nodding, etc., the operation is guaranteed to be a real living face.
The second step is the back-office social security face social security. After obtaining the entire face image in the live test API, the link will identify the ID card by scanning, and after getting the ID card avatar, the person on the face and the person on the ID card will be The face is compared and identified to determine whether it is the same face.
The live detection API technology can be operated on the mobile platform to provide the android and ios platform SDK. Since the face comparison algorithm has a very large amount of computation, it needs to be deployed on the server side, and currently supports mainstream platforms such as windows and linux.
Through social security social security and in-vivo detection API technology, it is very good to solve the risks and loopholes in the real-name authentication link.
Social Security Face Social Security, Live Testing API Product Background
With the application of the deep learning method, the recognition rate of social security face social security technology has been qualitatively improved. At present, the social security rate of social security has reached more than 99%. Compared with other biometrics technology, social security social security technology has its own unique advantages in practical applications: it can be directly accessed by the camera, and the identification process can be completed in a non-contact manner, which is convenient and quick. At present, our social security face social security technology has been applied in the fields of finance, education, scenic spots, travel, and social security.
Social Security Face Social Security, Live Testing API Product Profile
Social security face social security technology is mainly divided into two parts:
The first step is the front-end human face detection API, which mainly supports the android and ios platforms. At the front end, through the combination of blinking, opening, shaking, nodding, etc., the operation is guaranteed to be a real living face.
The second step is the back-office social security face social security. After obtaining the entire face image in the live test API, the link will identify the ID card by scanning, and after getting the ID card avatar, the person on the face and the person on the ID card will be The face is compared and identified to determine whether it is the same face.
The live detection API technology can be operated on the mobile platform to provide the android and ios platform SDK. Since the face comparison algorithm has a very large amount of computation, it needs to be deployed on the server side, and currently supports mainstream platforms such as windows and linux.
Through social security social security and in-vivo detection API technology, it is very good to solve the risks and loopholes in the real-name authentication link.