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This research paper presents a novel approach to real-time emotion detection using a neural network based on the FER2013 dataset. The proposed system is designed to help in monitoring the behavior of patients and assist in their mental health management. The accuracy of the proposed model is evaluated through extensive experiments and comparisons with other state-of-the-art models. The results demonstrate the effectiveness of the proposed approach in accurately detecting emotions in real-time. This paper provides a detailed description of the proposed system, the experimental setup, and the obtained results, and concludes with a discussion of the potential applications and future work. Overall, this research contributes to the development of a practical and effective system for real-time emotion detection and monitoring.
Aharnish et al. (Thu,) studied this question.