@inproceedings{675e0520ad724e3ebc3b8653bf903c59,
title = "The Analysis of CNN Structure for Image Denoising",
abstract = "This paper proposes an optimal structure of a convolutional neural network (CNN) for image denoising by analyzing the conventional CNN denoisers. There are three main factors that can determine the denoising performance of the CNN denoiser: the number of feature dimensions of each convolution layer, the number of convolution layers, and the usage of dilated convolution. We analyze the denoising performance variations of the conventional CNN denoiser depending on the above three factors and propose the optimal structure of the CNN denoiser. Experimental results showed that the above three factors have a high correlation with the denoising performance. Based on the experimental results, we could provide the optimal structure of the CNN denoiser.",
keywords = "Convolution neural network, Dilated convolution, Feature dimension, Image denoising",
author = "Park, {Jae Hyeon} and Kim, {Jeong Hyeon} and Cho, {Sung In}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 15th International SoC Design Conference, ISOCC 2018 ; Conference date: 12-11-2018 Through 15-11-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ISOCC.2018.8649916",
language = "English",
series = "Proceedings - International SoC Design Conference 2018, ISOCC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "220--221",
booktitle = "Proceedings - International SoC Design Conference 2018, ISOCC 2018",
address = "United States",
}