Classroom attendance supervision method and system based on TensorFlow framework and storage medium

Abstract

According to the classroom attendance supervision method and system based on the TensorFlow framework and the storage medium, student information is automatically crawled from an existing educationaladministration system and an existing student information system of a school, student identity information and daily class information are collected, face information of students is obtained in real time through a camera, and the student attendance supervision method and system based on the TensorFlow framework have the advantages of being high in practicability and easy to popularize and apply. Through a built-in training model, identity information of a student is automatically matched with each piece of face information, so that a series of problems of attendance data omission, substitute sign-in, slip after sign-in and the like are effectively solved, basic teaching management of schools is effectively improved, and the schools can automatically complete classroom roll calling and student lecture attending quality evaluation.

Description

technical field [0001] The present invention relates to the field of intelligent identification technology, in particular to a classroom attendance supervision method, system and storage medium based on the framework of TensorFlow. Background technique [0002] Nowadays, there are many "low-headed people" and "trunkers" in university classrooms. Bad behaviors such as being late, leaving early, absenteeism, skipping classes, playing with mobile phones and other bad behaviors will not only affect learning, but also affect the mood of teachers in class, and even disrespect for teachers' labor. . The current roll call system in colleges and universities adopts two technical methods: one uses fingerprint attendance machines combined with terminal software to realize student attendance statistics. The design collects, analyzes and compares students' fingerprints through special photoelectric conversion equipment and computer image processing technology, and can automatically, qui...

AI Technical Summary

Problems solved by technology

[0003] However, the traditional attendance method generally has the following disadvantages: fingerprint attendance recognition needs to be queued, and the efficiency is low. It is suitable for scenes with a small number of people and has a large environmental impact. Fingerprints are required to be clean. Dry, too cold, wet or peeling fingers will affect the punching effect. , easy to leak fingerprints; there is a deviation in the positioning of students in the mobile attendance application. It may happen that students arrive at the classroom but cannot check in. It is greatly affected by the speed of the network. If the classroom information is poor, it will affect the check in

[0004] Traditional attendance check-in technology is only suitable for regular check-in before, during or after class, and cannot monitor students' course attendance status in real time; traditional attendance check-in technology can only realize check-in and sign-in, and cannot analyze and supervise students' class status

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