EMOTION DETECTION USING FCM FOR CONTROLLING DEVICES
DOI:
https://doi.org/10.22159/ijet.2024v12.47386Keywords:
Neural Networks, Machine Learning, Fuzzy C-Means, WLD, Convolutional Neural NetworksAbstract
The human face is the most important and significant bodily part that contributes greatly to both human-to-human and human-to-machine communication. We always recognize a person by their face, from which we can infer their gender, extrapolate their age, and also deduce certain cultural traits. The technology we use most frequently today is face detection, and a number of programs need to be able to recognize emotions. The prevalent models do not use feelings to regulate device operation; instead, they rely on facial function identification from a whole image, which has a low accuracy level. The suggested module gathers photos from a camera or a database, recognizes faces, and then extracts features to build a powerful emotion detection tool for practical applications. Fuzzy clustering is used to identify different human emotions including happiness, sadness, and fear while managing the technology. These robust devices are made to be employed in successful human–computer interaction and human decisionmaking.
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Copyright (c) 2024 DHANALAKSHMI G, PRATHEEBHA S, THANAPPRIYA RL, MONIKA NS
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