# High-precision facial expression recognition

A facial expression recognition model based on ViT architecture, fine-tuned on the imagefolder dataset with an accuracy of 91.77%

A facial expression recognition model fine-tuned based on a pre-trained model, which can effectively recognize eight different facial expressions.

A ViT-based facial expression recognition model fine-tuned on FER2013, MMI, and AffectNet datasets, capable of recognizing seven basic emotions

ViT-based facial expression recognition model, fine-tuned on FER2013, MMI, and AffectNet datasets, supporting seven emotion classifications

Facial expression recognition model fine-tuned based on ResNet-50 architecture, trained on FER2013 and CKPlus datasets

This is an image classification model based on the BEiT architecture, fine-tuned on the FER2013 and CK+ datasets for facial expression recognition tasks.

A PyTorch-based facial emotion recognition model trained on the FER2013 dataset with an accuracy of 91.9%.