Robust spike-and-slab deep Boltzmann machines for face denoising

doi:10.1007/s00521-018-3866-6

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Robust spike-and-slab deep Boltzmann machines for face denoising
	Zhang, Nan 1,2; Ding, Shifei 1,2; Zhang, Jian 1,2; Zhao, Xingyu 1,2
刊名	NEURAL COMPUTING & APPLICATIONS
	2020-04-01
卷号	32 期号:7 页码:2815-2827
关键词	Restricted Boltzmann machine Deep Boltzmann machine Unsupervised learning Denoising
ISSN号	0941-0643
DOI	10.1007/s00521-018-3866-6
英文摘要	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.
WOS研究方向	Computer Science
语种	英语
出版者	SPRINGER LONDON LTD
WOS记录号	WOS:000522553100064
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/14020]
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.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China 2.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, 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.