A Deep Learning Powered System to Lie Detection While Online Study

Abstract

Many education facilities have recently switched to online learning due to the COVID-19 pandemic. The nature of online learning makes it easier for dishonest behaviors, such as cheating or lying during lessons. We propose a new artificial intelligence - powered solution to help educators solve this rising problem for a fairer learning environment. We created a visual representation contrastive learning method with the MobileNetV2 network as the backbone to improve predictability from an unlabeled dataset which can be deployed on low power consumption devices. The experiment shows an accuracy of up to 59%, better than several previous research, proving the usability of this approach.