Abstract
Human emotions can be understood from facial expressions, a type of nonverbal communication. Facial emotion recognition is a technology that analyzes emotions from various sources such as images and videos. Emotion recognition is an important topic due to its wide range of applications. In this paper, the YOLOv5 (You Look Only Once) model was used to detect basic human emotions. Capturing facial expressions aids to identify the emotion based on which various suggestions can be proposed, such as songs and movie recommendations. There are numerous models for emotion detection in different architectural styles. In this article, we present a less explored YOLOv5 model. It is more accurate and gives a real time result than the previous detection algorithms. 40 images from the FER2013 dataset were used to train our YOLOv5 model and accuracy of 50% was achieved with the proposed model.
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Shaikh, A., Kanojia, M., Mishra, K. (2023). Emotion Detection Based on Facial Expression Using YOLOv5. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-031-35501-1_21
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