基于混合自动编码器的分类应用
- 文章编号:
- 2096-1618(2016)增-0001-06
- 摘要:
- 自动编码器是一种无监督的深度学习模型,通过重构输入数据来提取数据特征。针对重构误差小但分类结果不一定好的问题,提出一种混合自动编码器模型。该方法在保证重构误差小的同时,使学习到的特征更有利于分类。实验结果表明,该方法对黑白和灰度图像的分类效果显著,准确率提高了1.5%～17%。
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备注/Memo
收稿日期:2016-02-19