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Faster Region Convolutional Neural Network(FRCNN)Based Facial Emotion Recognition

Computers, Materials & Continua 2024年第5期79卷 2427-2448页

作者： J.Sheril Angel A.Diana Andrushia TMary Neebha Oussama Accouche louai saker N.Anand Department of Electronics and Communication Engineering Karunya Institute of Technology and SciencesCoimbatore641114India College of Engineering and Technology American University of the Middle EastEgaila54200Kuwait Department of Civil Engineering Karunya Institute of Technology and SciencesCoimbatore641114India

Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective *** traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets,recent strides in artificial intelligence and deep learning(DL)have ushered in more sophisticated *** research aims to develop a FER system using a Faster Region Convolutional Neural Network(FRCNN)and design a specialized FRCNN architecture tailored for facial emotion recognition,leveraging its ability to capture spatial hierarchies within localized regions of facial *** proposed work enhances the accuracy and efficiency of facial emotion *** proposed work comprises twomajor key components:Inception V3-based feature extraction and FRCNN-based emotion *** experimentation on Kaggle datasets validates the effectiveness of the proposed strategy,showcasing the FRCNN approach’s resilience and accuracy in identifying and categorizing facial *** model’s overall performance metrics are compelling,with an accuracy of 98.4%,precision of 97.2%,and recall of 96.31%.This work introduces a perceptive deep learning-based FER method,contributing to the evolving landscape of emotion recognition *** high accuracy and resilience demonstrated by the FRCNN approach underscore its potential for real-world *** research advances the field of FER and presents a compelling case for the practicality and efficacy of deep learning models in automating the understanding of facial emotions.

关键词： Facial emotions FRCNN deep learning emotion recognition face CNN

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