Facial Expression Recognition Using Deep Learning: A Comprehensive Study on Methodologies and Applications
Year: 2025
Type: article
Abstract: This paper provides an extensive study on Recognition of facial expressions (FER) using advanced deep learning methods. We highlight the effectiveness of the relationship between long short-term memory and convolutional neural networks (CNNs) (LSTM) networks, which have shown remarkable accuracy in emotion classification tasks. Our proposed model achieved a validation accuracy of 96.24%, significantly outperforming existing models, particularly in recognizing subtle emotional variations. Additionally, we explore the integration of self-attention mechanisms to enhance feature extraction and improve recognition rates across diverse datasets, encompassing FER2013 and RAF-DB. The results highlight the potential of these methodologies in real-world applications, clearing the path for future advancements in emotion AI.
Authors: Yash Raj Suman, Sathiya Prakash, Varun M.B, Rohit Kumar
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6930462193
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