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1. 杭州电子科技大学计算机学院,浙江 杭州 310018
2. 杭州电子科技大学复杂系统建模与仿真教育部重点实验室,浙江 杭州 310018
[ "胡海洋(1977-),男,博士,杭州电子科技大学教授,主要研究方向为分布式系统、数据库技术、工作流技术。" ]
[ "许军(1990-),男,杭州电子科技大学硕士生,主要研究方向为数据库技术、图像检索。" ]
[ "胡华(1964-),男,博士,杭州电子科技大学教授,主要研究方向为分布式系统、数据库技术。" ]
网络出版日期:2016-04,
纸质出版日期:2016-04-20
移动端阅览
胡海洋, 许军, 胡华. 基于A-ELM的移动视觉搜索方法[J]. 电信科学, 2016,32(4):92-102.
Haiyang HU, Jun XU, Hua HU. Mobile visual searching method based on ascending extreme learning machine[J]. Telecommunication science, 2016, 32(4): 92-102.
胡海洋, 许军, 胡华. 基于A-ELM的移动视觉搜索方法[J]. 电信科学, 2016,32(4):92-102. DOI: 10.11959/j.issn.1000-0801.2016088.
Haiyang HU, Jun XU, Hua HU. Mobile visual searching method based on ascending extreme learning machine[J]. Telecommunication science, 2016, 32(4): 92-102. DOI: 10.11959/j.issn.1000-0801.2016088.
计算机智能技术在图像领域已经得到广泛的应用。极限学习机(ELM)作为一种新兴技术,克服了其他传统智能技术所面临的一些问题,吸引了越来越多研究人员的关注。首先对ELM算法的性能进行了分析验证,并将其延伸到图像分类搜索上。在此基础上,提出了基本视觉搜索(BMVS)框架,将ELM运用到此框架服务器端,并进一步优化了ELM的分类性能。最后实验证明ELM在移动视觉搜索方面的可行性,并通过和支持向量机(SVM)的实验对比验证相关方法的高效性。
Computer intelligence technology had been widely used in the field of image searching. Extreme learning machine has emerged as a new technology which overcomes the problems in traditional intelligent field and it has attracted more and more researchers. The algorithm performance of ELM was analyzed firstly,extending the method to image classification field. A basic mobile visual searching(BMVS)framework was proposed which applies ELM to image searching and optimizes the performance of ELM. Finally,the experiment proves the effectiveness of the method proposed by using ELM for the mobile vision searching. Through the experiments of comparison with SVM-based methods,the efficiency of the method proposed was also confirmed.
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