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>
개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.
벤치마크
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Dataset기록된 모델 예시MetricPaperCode
데이터셋
29개논문
Accuracy: 87.0%
Accuracy: 79.26%
Accuracy(on validation set): 59.27
Accuracy(on validation set): 51.181%
Accuracy(on validation set): 65.32%
Accuracy(on validation set): 55.17%
ICC: 0.67
Accuracy: 75.67
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