International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 5 September-October 2024 Submit your research before last 3 days of October to publish your research paper in the issue of September-October.

Facial Emotion Identification Using Convolution Neural Networks: Enhancing Human-Computer Interaction

Author(s) Sonia Rani, Ravinder Kaur, Abhishek Kaleroun, Abhishek Gatyan, Dharminder yadav
Country India
Abstract Facial Emotion identification uses technology to classify the various emotions of humans. Human-Computer Interaction is an emerging field that uses deep learning algorithms to classify human feelings. Convolution Neural Networks (CNN) are the groundbreaking technology to process images in an efficient manner. This paper explores deep learning models on FER-2013 dataset for emotion prediction to analyze facial expression and classify them into different emotions such as Angry, Disgust, Fearful, Happy, Sad, Surprise and Neutral. Convolutional Neural Network (CNN) and ResNet-50 are the two architectures used for this research work. Both the models were trained at 35 epochs. CNN gives 97.83% accuracy and ResNet-50 gives 97.74% accuracy on the FER-2013 dataset. Thus, the result shows that both models are doing well in learning from training data and even have nearly the same performance. The findings of the study hence emphasizes that CNN models have high potential for performing efficient and accurate emotion recognition, but they still require more improvement in terms of generalization on unseen data.
Keywords CNN, ResNet-50, FER-2013, Emotion, Machine learning, Deep-learning
Field Engineering
Published In Volume 6, Issue 5, September-October 2024
Published On 2024-09-10
Cite This Facial Emotion Identification Using Convolution Neural Networks: Enhancing Human-Computer Interaction - Sonia Rani, Ravinder Kaur, Abhishek Kaleroun, Abhishek Gatyan, Dharminder yadav - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.27374
DOI https://doi.org/10.36948/ijfmr.2024.v06i05.27374
Short DOI https://doi.org/gwfgfz

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