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
Source PublicationINTELLIGENT COMPUTING IN SIGNAL PROCESSING AND PATTERN RECOGNITION
2006
Volume345Pages:430-439
SubtypeArticle
AbstractThe 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 HeadingsScience & Technology ; Technology
WOS KeywordSEGMENTATION ; CONSTRAINTS ; SUBJECT
Indexed ByISTP ; SCI
Language英语
WOS Research AreaAutomation & Control Systems ; Computer Science ; Engineering
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000240385300044
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9298
Collection09年以前成果
AffiliationChinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
Recommended Citation
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.
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