Deep-learning and cloud service-based face identification attendance system and method

Abstract

The invention discloses a deep-learning and cloud service-based face identification attendance system and method. The system comprises a face detection module, a data wireless transmission module, a cloud server and an attendance information management webpage, wherein the face detection module is connected with the data wireless transmission module; the data wireless transmission module is connected with the cloud server via network; a deep-learning network training module is established in the cloud server, face images are pre-trained, and feature vectors are saved; face images are extracted and transmitted to the cloud by virtue of the face detection module and the data wireless transmission module, and is input into the deep-learning network training module as a testing sample to match with faces, the match result is saved to a database, and the attendance information management webpage is interacted with the database to acquire attendance information. According to the system and method, matching identification is prevented from being performed in mass data by classified storage and classified calling, so that storage efficiency and matching identification efficiency can be improved, and the system has better robustness and higher efficiency.

Description

technical field [0001] The invention relates to the technical field of attendance equipment, in particular to a face recognition attendance system and method based on deep learning and cloud services. Background technique [0002] At present, manual attendance is the main way of checking attendance in colleges and universities. This attendance method is time-consuming, and it is easy to take attendance on behalf of others, which affects the teaching management behavior of colleges and universities. Some colleges and universities have introduced radio frequency identification attendance and fingerprint attendance. However, the radio frequency identification attendance is very easy to replace the attendance, and the fingerprint attendance has health risks, and needs to be queued for attendance. Therefore, the above two attendance methods have not been favored by the educational administration departments of universities. . [0003] Face recognition attendance is an attendance...

AI Technical Summary

Problems solved by technology

[0002] At present, manual attendance is the main way of checking attendance in colleges and universities. This attendance method is time-consuming, and it is easy to take attendance on behalf of others, which affects the teaching management behavior of colleges and universities. Some colleges and universities have introduced radio frequency identification attendance and fingerprint attendance. However, the radio frequency identification attendance is very easy to replace the attendance, and the fingerprint attendance has health risks, and needs to be queued for attendance. Therefore, the above two attendance methods have not been favored by the educational administration departments of universities.

[0003] Face recognition attendance is an attendance method that has gradually emerged in recent years. It mainly completes sign-in by recognizing faces and performing feature matching; moreover, the existing face recognition attendance machines have the defects of low recognition rate and small face storage capacity. It cannot be systematically applied to college attendance. The existing face recognition attendance machine fails to connect the educational administration department with the attendance system, and the educational affairs management department cannot check the student's attendance status online. Therefore, if the existing face recognition attendance Colleges and universities cannot substantially improve the efficiency of educational administration management

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