Enhanced CNN for image denoising
Enhanced CNN for image denoising
About this item
Full title
Author / Creator
Tian, Chunwei , Xu, Yong , Fei, Lunke , Wang, Junqian , Wen, Jie and Luo, Nan
Publisher
Beijing: The Institution of Engineering and Technology
Journal title
Language
English
Formats
Publication information
Publisher
Beijing: The Institution of Engineering and Technology
Subjects
More information
Scope and Contents
Contents
Owing to the flexible architectures of deep convolutional neural networks (CNNs) are successfully used for image denoising. However, they suffer from the following drawbacks: (i) deep network architecture is very difficult to train. (ii) Deeper networks face the challenge of performance saturation. In this study, the authors propose a novel method...
Alternative Titles
Full title
Enhanced CNN for image denoising
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_wiley_primary_10_1049_trit_2018_1054_CIT2BF00055
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_wiley_primary_10_1049_trit_2018_1054_CIT2BF00055
Other Identifiers
ISSN
2468-2322
E-ISSN
2468-2322
DOI
10.1049/trit.2018.1054
