Performing facial recognition using ensemble learning

Publication Name

Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science


Investment in facial recognition technologies has increased recently with the amount of venture capital invested in facial recognition startups dramatically increasing in 2021. Facial recognition uses AI and ML techniques to find human faces in the surrounding area. Facial recognition technology is used by the web application Automated Attendance System (AAS) which was developed by a group of students from the University of Wollongong in Dubai to automate attendance management in educational institutions. AAS is simple to use, quick to implement, and can be incorporated into current educational institutions. Deep convolutional neural networks, notably the VGG19 and EfficientNetB0 models, are the foundation of the system. These models were trained for high accuracy utilizing transfer learning and ensemble learning. The automation of attendance tracking reduces human error; increases efficiency, accuracy, and integrity; and does away with the need for manual methods of collecting attendance.

Open Access Status

This publication is not available as open access

First Page


Last Page




Link to publisher version (DOI)