Accuracy(on validation set): 65.5%
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Facial Expression Recognition (FER)
Facial Expression Recognition (FER) is a computer vision task aimed at identifying and categorizing emotional expressions depicted on a human face. The goal is to automate the process of determining emotions in real-time, by analyzing the various features of a face such as eyebrows, eyes, mouth, and other features, and mapping them to a set of emotions such as anger, fear, surprise, sadness and happiness.
<span style="color:grey; opacity: 0.6">( Image credit: DeXpression )</span>
논문
UAR: 79.0
Accuracy: 87.0%
Accuracy (7 emotion): 99.7
Accuracy (7 emotion): 99.8
0..5sec: sa
Accuracy (8 emotion): 100
Accuracy (7 emotion): 98
Accuracy: 98.63
Accuracy (10-fold): 89.6
Accuracy (8 emotion): 96.8Accuracy (7 emotion): -Accuracy (6 emotion): 98.6
Accuracy: 79.26%
Accuracy(on validation set): 59.27
Accuracy: 82.74%
Accuracy(on validation set): 65.32%
Accuracy: 54.82%
Accuracy(on validation set): 55.17%
Accuracy (7 emotion): 100.00
Accuracy (10-fold): 84.59
Accuracy: 75.67
Accuracy : 85.87
Accuracy (7 emotion): 98.23