Relaxation Labeling using an improved Hopfield neural network

CASIA OpenIR > 09年以前成果

	Relaxation Labeling using an improved Hopfield neural network
	Cheng, Long; Hou, Zeng-Guang; Tan, Min; Huang, DS; Li, K; Irwin, GW
发表期刊	INTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION
	2006
卷号	345 页码:430-439
文章类型	Article
摘要	The relaxation labeling is a useful technique to deal with local ambiguity and achieve consistency. In [1], some useful comments indicate several common properties exist in the relaxation process and the neural network technique. Neural networks can be used as an efficient tool to optimize the average local consistency function whose optimal solution results in a compatible label assignment. However, most of current investigations in this field are based on the standard Hopfield neural network (SHNN) presented in [2]. In this paper, an improved Hopfield neural network (IHNN) presented in [3] is utilized to fulfill relaxation labeling. Compared to the SHNN, this approach has some advantages. 1) The IHNN uses fewer neurons than that of SHNN. 2) The activation function of IHNN is easier to be implemented than that of SHNN. 3) The IHNN does not contain any penalty parameters. It can generate the exact optimal solution. Some experimental results illustrate that the IHNN approach can obtain a better labeling performance than that of SHNN.
WOS标题词	Science & Technology ; Technology
关键词[WOS]	SEGMENTATION ; CONSTRAINTS ; SUBJECT
收录类别	ISTP ; SCI
语种	英语
WOS研究方向	Automation & Control Systems ; Computer Science ; Engineering
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS记录号	WOS:000240385300044
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/9298
专题	09年以前成果
作者单位	Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Cheng, Long,Hou, Zeng-Guang,Tan, Min,et al. Relaxation Labeling using an improved Hopfield neural network[J]. INTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION,2006,345:430-439.
APA	Cheng, Long,Hou, Zeng-Guang,Tan, Min,Huang, DS,Li, K,&Irwin, GW.(2006).Relaxation Labeling using an improved Hopfield neural network.INTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION,345,430-439.
MLA	Cheng, Long,et al."Relaxation Labeling using an improved Hopfield neural network".INTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION 345(2006):430-439.