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Facialemorecog
F
Facialemorecog
Developed by Rajaram1996
A PyTorch-based facial emotion recognition model trained on the FER2013 dataset with an accuracy of 91.9%.
Downloads 628
Release Time : 3/2/2022
Model Overview
This model focuses on facial emotion recognition tasks, capable of classifying facial expressions in input images, suitable for various emotion analysis applications.
Model Features
High accuracy
Achieves 91.9% classification accuracy on the FER2013 dataset
Strong generalization
Suitable for custom image classification needs in any scenario
Open-source license
Adopts the MIT license, allowing free use and modification
Model Capabilities
Facial emotion recognition
Image classification
Expression analysis
Use Cases
Affective computing
User emotion analysis
Analyze changes in users' facial expressions during interaction
Can be used to improve user experience or provide emotional feedback
Psychological research
Emotional response study
Record and analyze subjects' emotional responses to stimuli
Provides quantitative data for psychological research
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