Dynamic and static models for real-time facial emotion recognition
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Updated
Aug 2, 2024 - Jupyter Notebook
Dynamic and static models for real-time facial emotion recognition
Face Expression Recognition with ensemble for InceptionV3, ResNet50, MobileNetV2
The PyTorch implementation of Discriminant Distribution-Agnostic loss (DDA loss)
In this repo, I implemented VGGNet, MobileNet and AlexNet and compared their performance on Emotion Detection Task using AffectNet dataset.
An academic research project for comparative analysis of deep learning models in facial emotion recognition.
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