Pytorch实现基于卷积神经网络的面部表情识别项目源码+面部表情数据集+论文+答辩PPT.zip

上传者: 55305220 | 上传时间: 2022-06-10 14:06:38 | 文件大小: 128.45MB | 文件类型: ZIP
Pytorch实现基于卷积神经网络的面部表情识别项目源码+论文+答辩PPT 本项目是一个非常完整的深度学习实践,是基于卷积神经网络模型开展表情识别的研究,使用到的模型是卷积神经网络,难度适中,初学者也可看懂。为了尽可能的提高最终表情识别的准确性,需要大量的样本图片训练,优化,所以采用了 FER2013 数据集用来训练、测试,此数据集由 35886 张人脸表情图片组成,其中,测试图 28708 张,公共验证图和私有验证图各 3589 张,所有图片中共有7种表情。 源代码方便大家开箱即用! 动手完成这个项目之后,就可以学习到: 1. 深度学习中CNN(卷积神经网络)的使用,为之后学习相关神经网络模型做了很好的铺垫。 2. 学会使用深度学习框架之一Pytorch的使用。 3. 多分类问题在实际中的应用,是二分类的扩展。 4. 从数据处理,可视化,到模型搭建的过程,是一种经验和技巧的积累,达到“举一反三”的效果。

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