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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>
개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.
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Dataset기록된 모델 예시MetricPaperCode
데이터셋
29개논문
Accuracy (8 emotion): 100
Accuracy: 87.0%
Accuracy (7 emotion): 98
Accuracy (8 emotion): 96.8Accuracy (7 emotion): -Accuracy (6 emotion): 98.6
Accuracy: 79.26%
Accuracy (7 emotion): 99.7
UAR: 79.0
Accuracy (7 emotion): 99.8
Accuracy (7 emotion): 100.00
Accuracy : 85.87
Accuracy (7 emotion): 98.23
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