Recognizing facial emotions is crucial to comprehending human behavior and enhancing intelligent systems.[12] Previous studies have shown that facial expression analysis for emotion recognition tasks can be accomplished with machine learning techniques [4]. Inspired by these studies, this work introduces a Convolutional Neural Network (CNN)-based facial emotion detection system. The main goal of the suggested system is to automatically recognize emotions from facial images, including happy, sad, angry, fear, surprise, disgust, and neutral. The model is trained and assessed using the FER-2013 dataset. To increase learning efficiency, image preprocessing methods like grayscale conversion, resizing, and normalization are used before classification. To precisely extract the facial region, a Haar Cascade classifier is employed for face detection. According to experimental evaluation, the CNN-based method outperforms conventional feature-based methods and achieves dependable accuracy. The outcomes demonstrate the efficacy of deep learning models for applications involving facial emotion recognition.
Keywords
Face Detection, Convolutional Neural Network, Deep Learning, FER-2013 Dataset, Facial Emotion Recognition, Image Preprocessing, and Machine Learning
Conclusion
In this paper, a facial emotion recognition system using a Convolutional Neural Network (CNN) has been discussed. The proposed system is very efficient in recognizing facial expressions and categorizing them into various types of emotions like happy, sad, angry, fear, surprise, disgust, and neutral. Image processing and facial recognition methods are used to increase the efficiency of the system. The experimental outcome shows that the proposed system using CNN is more efficient than the conventional feature-based approaches. This paper proves that deep learning methods can be effectively used for facial emotion recognition.
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How to Cite This Paper
Aluri Mahendra Chowdary, Bapathi Madhu Sudhan Reddy, Chittamuri Chaitanya, Ms.Neelavani (2026). A Robust Deep Learning Model for Multi-Class Facial Emotio Recognition. International Journal of Computer Techniques, 13(2). ISSN: 2394-2231.
