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Automated Attendance System Using Deep Learning

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dc.contributor.author Al-Mahmud, Zubayer
dc.date.accessioned 2022-01-15T05:41:46Z
dc.date.available 2022-01-15T05:41:46Z
dc.date.issued 2021-06-03
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6756
dc.description.abstract In this modern age Attendance System becomes automated thanks to time saving, efficient and useful method decreasing administration’s and organization’s strain. Attendance system is important to classroom evaluation, population and workforce management. Caused by the event of technology, computer scientists are share a keen interest during this area. Currently there are several technologies based attendance system but we always discuss more sufficient system saving time and toil. During this case, the deep learning approach is far more convenient than others. In naive words, it's a computer aided system for automatically identifying an individual from a true time image or video frame. During this paper we proposed an automatic attendance system using Deep Learning Algorithm(s). This approach can help to reduce the complexity of taking attendance for the teachers as the procedure is fully automated and algorithms dependent. In this report we explain an automatic attendance procedure with the collaboration of two deep learning algorithms Faster R-CNN and SeetaFace. Output brings four short similarity situation of classroom like absence, delayed appearances, early leave, unauthorized entry during course session and passes the knowledge to attendance sheet which will evaluate the students/persons. A high definition camera setup capturing real time to identify/recognize the authorized person. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Deep learning en_US
dc.subject Automated system en_US
dc.subject Attendance en_US
dc.title Automated Attendance System Using Deep Learning en_US
dc.type Article en_US


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