Shivamma D¹, Nitheesh Kumar G²*, Deepika P², Dr. Shreedhara K S²

¹Assistant Professor, Dept. of CSE(DS), School of Engineering, DSU, India
²PG Student, Dept. of CSE UBDT College of Engineering, VTU, Davanagere, India

*Corresponding Author: Nitheesh Kumar G, PG Student, Dept. of CSE UBDT College of Engineering, VTU, Davanagere, India.

Received: May 21, 2024; Published: June 09, 2025

Abstract

A face detection model based on the mapping of behaviors with physical aspects is offered by the facial emotion recognition system described in this study. Geometric structures that have been reconstructed serve as the foundation matching template for the identification system and are linked to the physical characteristics of the human face that correspond to different expressions including happy, sad, fear, angry, surprise, and disgust. These days, face expression recognition is popular due to its broad range of applications. Because of its many uses, emotion recognition is widely used. As the science of learning has advanced, emotion detection has become increasingly important in business. Feeling recognition allows one to perceive a person's feelings. To detect emotional states in pictures, several methods have been developed.

Keywords: CNN (Convolutional Neural Network); LBP (Local Binary Patterns); Emotion Detection; Facial Expression; SVM (Support Vector Machine); KNN (K-Nearest Neighbor)

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Citation

Citation: Shreedhara KS., et al. “Convolution Neural Network Approaches for Facial Emotion Recognition".Acta Scientific Computer Sciences 7.3 (2025): 14-19.

Copyright

Copyright: © 2025 Shreedhara KS., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.