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Design And Implementation Of Enterprise Attendance Management System Based On SpringBoot And Face Recognition

Posted on:2024-01-16Degree:MasterType:Thesis
Country:ChinaCandidate:T WangFull Text:PDF
GTID:2568307082962299Subject:Computer technology
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With the continuous development of information technology,the methods of attendance management are becoming increasingly diverse,and traditional attendance methods can no longer meet the needs of intelligent management in enterprises.Applying facial recognition technology to enterprise attendance can effectively solve the problems existing in traditional attendance modes due to its own advantages.However,traditional facial detection and recognition algorithms also have some drawbacks,such as reduced recognition accuracy under changes in the external environment.Therefore,designing a robust and fast and accurate enterprise attendance management system for facial recognition is the direction of this article’s research.This article adopts a face recognition technology based on a dual layer framework of face detection and recognition,using the FaceNet algorithm for face recognition,including the MTCNN algorithm for face detection.Finally,the algorithm is combined with the SpringBoot framework to design an attendance management system for small and medium-sized enterprises.The main work content is as follows:(1)For the real-time facial detection part in the camera,some improvements have been made on the original MTCNN algorithm model,allowing the model to effectively detect the position of facial regions and key feature points in low light or partial occlusion,improving the model’s adaptability to the environment.(2)Adopting FaceNet facial recognition algorithm.Map each face image processed by MTCNN into a high-dimensional Euclidean space,calculate the Euclidean distance between these vectors,and return the recognition results through SVM classifier.Among them,the backbone feature extraction network of FaceNet uses Inception ResNet V1 to complete the feature extraction of face images,uses Triplet Loss as the loss function in the training process,and uses LFW data set for effect testing..(3)Embed the algorithm into the SpringBoot framework for system construction,using a MySQL database.After analyzing the needs of the enterprise,the system framework and functions were designed.The system’s functional modules mainly include user management,attendance management,facial image acquisition,and facial recognition modules.These functions enable administrators to effectively analyze and manage employee attendance data.Finally,the various functions of the system are tested.The test results show that the identification method proposed in this paper and the attendance system designed can meet the enterprise attendance task in complex environment,and has high application value.
Keywords/Search Tags:SpringBoot framework, Deep learning, Face recognition, Attendance management
PDF Full Text Request
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