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Project PPT_Format.pptx
1. Submitted in the partial fulfillment for the award of
the degree of
BACHELOR OF ENGINEERING
IN
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
DISCOVER . LEARN . EMPOWER
Department of AIT-CSE
Facial Emotion Detection Using
Neural Network
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Submitted by:
Aniket Kumar: 21BCS10906
Abdullah Khan: 21BCS10510
Harsh Pundhir: 21BCS5238
Under the Supervision of:
Mr. Sukhpreet Singh
2. Outline
โข Introduction to Project
โข Problem Formulation
โข Objectives of the work
โข Methodology used
โข Results and Outputs
โข Conclusion
โข Future Scope
โข References
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3. Introduction to Project
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โข Facial emotion detection is a technique used to analyze and recognize
human emotions from facial expressions.
โข This technique involves training a neural network to recognize various
facial features, such as eye movements, mouth shape, and eyebrow
position, which can then be used to classify emotions such as
happiness, sadness, anger, and surprise.
โข Neural networks are a popular machine learning algorithm used in
facial emotion detection due to their ability to learn the complex
pattern and relationships from data.
5. Objectives of the Work
โข Accurate Emotion Reorganization.
โข Improve Human-Robot Interactions.
โข Early detection of mental health issues.
โข Enhance Virtual and Argument Reality Systems.
โข Personalize User Experience.
โข Automation of Emotion Reorganization.
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6. Conclusion
โข Neural Networks are effective in detecting facial emotions with high
accuracy and speed.
โข Largest datasets can improve the accuracy of facial emotion
detection.
โข Preprocessing techniques, such as face detection and alignment, can
enhance the accuracy of facial emotion detection.
โข The selection of appropriate features and neural network architecture
can significantly impact the accuracy of facial emotion detection.
โข Facial emotion detection using neural networks can aid in
understanding human emotions and behavior.
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