Institute of Computing Technology, Chinese Academy IR
Robust spike-and-slab deep Boltzmann machines for face denoising | |
Zhang, Nan1,2; Ding, Shifei1,2; Zhang, Jian1,2; Zhao, Xingyu1,2 | |
2020-04-01 | |
发表期刊 | NEURAL COMPUTING & APPLICATIONS |
ISSN | 0941-0643 |
卷号 | 32期号:7页码:2815-2827 |
摘要 | The robust Gaussian restricted Boltzmann machine can effectively learn the structure of noise to achieve better results in the face denoising task. The robust Gaussian restricted Boltzmann machine model contains two types of the restricted Boltzmann machine (RBM) model, where a general RBM is used to model the structure of the noise and a Gaussian RBM is used to model the clean data. The spike-and-slab RBM shows better learning abilities than the Gaussian RBM in real images modeling. In addition, the deep Boltzmann machine (DBM) shows powerful image reconstruction ability. To model the real images better, we first stack the spike-and-slab RBM and the RBM to create the spike-and-slab DBM. And then, we utilize the spike-and-slab DBM instead of the Gaussian RBM to model the density of the clean data in the Robust Gaussian RBM, and the proposed method is named as the robust spike-and-slab DBM which can obtain clearer denoising images. Finally, in order to obtain better denoising results, we make use of the learned spike-and-slab DBM model and the mean field method to multi-inference the denoising data learned from the robust spike-and-slab DBM. Experimental results show that the robust spike-and-slab DBM is an effective neural network denoising method. |
关键词 | Restricted Boltzmann machine Deep Boltzmann machine Unsupervised learning Denoising |
DOI | 10.1007/s00521-018-3866-6 |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000522553100064 |
出版者 | SPRINGER LONDON LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/14021 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Ding, Shifei |
作者单位 | 1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China 2.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Nan,Ding, Shifei,Zhang, Jian,et al. Robust spike-and-slab deep Boltzmann machines for face denoising[J]. NEURAL COMPUTING & APPLICATIONS,2020,32(7):2815-2827. |
APA | Zhang, Nan,Ding, Shifei,Zhang, Jian,&Zhao, Xingyu.(2020).Robust spike-and-slab deep Boltzmann machines for face denoising.NEURAL COMPUTING & APPLICATIONS,32(7),2815-2827. |
MLA | Zhang, Nan,et al."Robust spike-and-slab deep Boltzmann machines for face denoising".NEURAL COMPUTING & APPLICATIONS 32.7(2020):2815-2827. |
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