泛读论文：Facial Expression Recognition 表情识别合集
基于跨链接 LeNet-5 网络的面部表情识别 自动化学报 2018.1html 问题web 传统的表情识别方法须要进行复杂的人工特征提取 为避免人为因素对表情特征提取产生的影响, 本文选择卷积神经网络 方法express 采用改进的 LeNet-5 即将网络结构中提取的低层次特征与高层次特征相结合构造分类器 JAFFE 94.37% CK+ 83.74% 参考网络 http://www.aas.
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相关文章
- 1. 2020tip表情识别论文Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition解读
- 2. 论文笔记 Deep Facial Expression Recognition: A Survey深度面部表情识别调查
- 3. 表情识别入门：ECCV2016《Peak-Piloted Deep Network for Facial Expression Recognition》
- 4. 表情识别综述2018-Deep Facial Expression Recognition: A Survey
- 5. 人脸表情识别，即FER(Facial Expression Recognition)
- 6. Facial Expression Recognition Using KCCA
- 7. Facial Expression Recognition by De-expression Residue Learning-论文笔记
- 8. Joint Pose and Expression Modeling for Facial Expression Recognition 论文翻译
- 9. Deep Covariance Descriptors for Facial Expression Recognition
- 10. Deep Facial Expression Recognition: A Survey