@inproceedings{scholars10160, title = {How's the Turnout to the Class? A Face Detection System for Universities}, pages = {179--184}, doi = {10.1109/IC3e.2018.8632630}, journal = {2018 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2018}, year = {2018}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, note = {cited By 4; Conference of 2018 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2018 ; Conference Date: 21 November 2018 Through 22 November 2018; Conference Code:144763}, isbn = {9781538672631}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062845819&doi=10.1109\%2fIC3e.2018.8632630&partnerID=40&md5=b20a88c199cd283b05525e4289e412b8}, abstract = {Intelligent classroom has been a trending topic in many institutions. Currently the chosen university for this study is using QR code attendance system. However, this QR code system has its own limitation as it needs a stable internet connection to generate QR code and verify attendance. Moreover, students who are not in the class still can verify their attendance by getting the picture of the QR code. The ability to create a new system with the existence of technology is beyond immediate needs. Therefore, aiming at an automatic class attendance system and ensure the attendance of the students, video monitoring techniques and automatic face detection is used to get the accuracy of the total students in the class and automatic identify who attend the class. The rapid development of technology provides many ways of detecting and recognizing faces detection based on the video monitoring. This system should be implemented as it is an important part of teaching management to a great assessment of teaching quality. It also eases the process of attendance report for international students to renew their visa as it is a mandatory document to be submitted to Education Malaysia Education Services (EMGS). {\^A}{\copyright} 2018 IEEE.}, keywords = {Codes (symbols); Face recognition, A-stable; Accuracy; Attendance systems; Automatic face detection; Code system; Face detection system; Internet connection; QR codes; Trending topics; Video monitoring, Students}, author = {Savita, K. S. and Hasbullah, N. A. and Taib, S. M. and Abidin, A. I. Z. and Muniandy, M.} }