文章基本信息

标题：Deep Learning for Image Denoising
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作者：HuiMing Li
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：3
页码：171-180
DOI：10.14257/ijsip.2014.7.3.14
出版社：SERSC
摘要：Deep learning is an emerging approach for finding concise, slightly higher level representations of the inputs, and has been successfully applied to many practical learning problems, where the goal is to use large data to help on a given learning task. We present an algorithm for image denoising task defined by this model, and show that by training on large image databases we are able to outperform the current state-of-the-art image denoising methods.
关键词：deep learning; image denoising; denoising auto-encoder