论文标题
深度学习的面部表情识别
Facial Expression Recognition with Deep Learning
论文作者
论文摘要
人们交流的最普遍的方式之一是通过面部表情。在本文中，我们进行了深入的潜水，实施了多个深度学习模型，以实现面部表达识别（FER）。我们的目标是双重的：我们的目标不仅是为了最大程度地提高准确性，还要将我们的结果应用于现实世界。通过利用最近的研究中的许多技术，我们证明了FER2013测试集的最新精度为75.8％，表现优于所有现有出版物。此外，我们展示了一个移动网络应用程序，该应用程序可以实时运行我们的FER模型。
One of the most universal ways that people communicate is through facial expressions. In this paper, we take a deep dive, implementing multiple deep learning models for facial expression recognition (FER). Our goals are twofold: we aim not only to maximize accuracy, but also to apply our results to the real-world. By leveraging numerous techniques from recent research, we demonstrate a state-of-the-art 75.8% accuracy on the FER2013 test set, outperforming all existing publications. Additionally, we showcase a mobile web app which runs our FER models on-device in real time.
