Face Recognition and Physiological Signal for Impaired Drivers: A Review

Seong, Lee Jian; Yogarayan, Sumendra; Razak, Siti Fatimah Abdul; Azman, Afizan

doi:10.1109/icoict58202.2023.10262615

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2024

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“…Additionally, in the future work live detection should be considered to avoid attendance forging using still images. Moreover, other applications of face recognition like recognition of driver who is driving under alcohol influence [19] or as assistive technology for visually impaired individuals [20] are to be explored.…”

Section: Discussionmentioning

confidence: 99%

Development of Automated Attendance System Using Pretrained Deep Learning Models

Ahmad,

Ab. Aziz,

Ghazali

2024

IJORAS

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- Smart classroom enables better learning experience to the students and aid towards efficient campus' management. Many studies have shown positive correlation between attendance and student's performance, where the higher the attendance, the better the student's performance. Therefore, many higher learning institutions make class attendance compulsory and students' attendance are recorded. Technological solutions for an advanced attendance system such as face recognition is highly desirable. The authenticity of attendance can be ensured by using such solution. In this work, artificial intelligence based face recognition system is used for attendance recording system. The recognized face is used to confirm the presence of a student to the class. Six pretrained face recognition model are evaluated for the adoption in the system developed. The FaceNet, is adopted in this work with accuracy of more than 95%. The automation system is supported by IoT.

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Section: Discussionmentioning

confidence: 99%