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- W4289752015 abstract "This paper presents a classifier ensemble for Facial Expression Recognition (FER) based on models derived from transfer learning. The main experimentation work is conducted for facial action unit detection using feature extraction and fine-tuning convolutional neural networks (CNNs). Several classifiers for extracted CNN codes such as Linear Discriminant Analysis (LDA), Support Vector Machines (SVMs) and Long Short-Term Memory (LSTM) are compared and evaluated. Multi-model ensembles are also used to further improve the performance. We have found that VGG-Face and ResNet are the relatively optimal pre-trained models for action unit recognition using feature extraction and the ensemble of VGG-Net variants and ResNet achieves the best result." @default.
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- W4289752015 date "2018-07-19" @default.
- W4289752015 modified "2023-10-01" @default.
- W4289752015 title "Transfer Learning for Action Unit Recognition" @default.
- W4289752015 doi "https://doi.org/10.48550/arxiv.1807.07556" @default.
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