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الرئيسية
SOTA
Facial Expression Recognition
Facial Expression Recognition On Fer2013
Facial Expression Recognition On Fer2013
المقاييس
Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Accuracy
Paper Title
Repository
Segmentation VGG-19
75.97
A novel facial emotion recognition model using segmentation VGG-19 architecture
Ensemble ResMaskingNet with 6 other CNNs
76.82
Facial Expression Recognition using Residual Masking Network
CNN Hyperparameter Optimisation
72.16
Convolutional Neural Network Hyperparameters optimization for Facial Emotion Recognition
ResEmoteNet
79.79
ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognition
Ad-Corre
72.03
Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the Wild
-
Mini-ResEmoteNet (B)
70.20
Mini-ResEmoteNet: Leveraging Knowledge Distillation for Human-Centered Design
-
Local Learning Deep+BOW
75.42
Local Learning with Deep and Handcrafted Features for Facial Expression Recognition
-
LHC-Net
74.42
Local Multi-Head Channel Self-Attention for Facial Expression Recognition
EmoNeXt
76.12
EmoNeXt: an Adapted ConvNeXt for Facial Emotion Recognition
Mini-ResEmoteNet (A)
76.33
Mini-ResEmoteNet: Leveraging Knowledge Distillation for Human-Centered Design
-
Regularized Xception with Step Decay Learning
94.34
Regularized Xception for facial expression recognition with extra training data and step decay learning rate
ResNet18 With Tricks
73.70
Fer2013 Recognition - ResNet18 With Tricks
Local Learning BOW
67.48
Challenges in Representation Learning: A report on three machine learning contests
VGGNet
73.28
Facial Emotion Recognition: State of the Art Performance on FER2013
Residual Masking Network
74.14
Facial Expression Recognition using Residual Masking Network
DeepEmotion
70.02
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network
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