Emotion Detection from Facial Expressions Using Deep Learning

Facial expression detection is a crucial aspect of human-computer interaction, enabling machines to recognize and respond to human emotions effectively. This paper presents a deep learning- based face expression detection system that classifies human emotions based on facial expressions. By leveraging convolutional neural networks (CNNs) and advanced image processing techniques, the system achieves high accuracy in detecting expressions such as happiness, sadness, anger, surprise, and neutrality. The research explores various datasets, training methodologies, and evaluation metrics to optimize performance. Keywords— Facial expression detection, deep learning, convolutional neural networks, emotion recognition, image processing, human-computer interaction, sentiment analysis, machine learning, facial recognition.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-15
DOI
https://doi.org/10.55041/ijsrem44585
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Emotion Detection from Facial Expressions Using Deep Learning

Vinod Narayanan, M. Vinuthna
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Emotion and Mood Recognition
article

Emotion Detection from Facial Expressions Using Deep Learning

Vinod Narayanan, M. Vinuthna
article en

Abstract

Facial expression detection is a crucial aspect of human-computer interaction, enabling machines to recognize and respond to human emotions effectively. This paper presents a deep learning- based face expression detection system that classifies human emotions based on facial expressions. By leveraging convolutional neural networks (CNNs) and advanced image processing techniques, the system achieves high accuracy in detecting expressions such as happiness, sadness, anger, surprise, and neutrality. The research explores various datasets, training methodologies, and evaluation metrics to optimize performance. Keywords— Facial expression detection, deep learning, convolutional neural networks, emotion recognition, image processing, human-computer interaction, sentiment analysis, machine learning, facial recognition.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
G Pulla Reddy Dental College & Hospital (IN)
Openalex Percentile: Top 93%
Emotion and Mood Recognition
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