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The central aim is to design a system that accurately classifies human emotions from live video streams using deep learning.

March 2, 2026Open Access

Real Time Facial Emotion Recognition Using Deep Learning

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The central aim is to design a system that accurately classifies human emotions from live video streams using deep learning.
Implemented a three-stage framework: face detection, pre-processing, and emotion classification.
Utilized convolutional neural networks for feature extraction and emotion classification.
Applied transfer learning with pre-trained models fine-tuned on benchmark datasets.
Achieved high accuracy in emotion recognition under variable conditions.
Maintained real-time processing speed during evaluations.
Demonstrated reliable performance across diverse facial expressions and orientations.

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Demonstrates a system that accurately detects emotions in real-time video streams, highlighting potential applications in various fields.

Ms.N.Sowmiya et al. (2026) studied this question.

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