Content-based image retrieval system using neural network

H. Karamti, M. Tmar, F. Gargouri
{"title":"Content-based image retrieval system using neural network","authors":"H. Karamti, M. Tmar, F. Gargouri","doi":"10.1109/AICCSA.2014.7073271","DOIUrl":null,"url":null,"abstract":"Visual information retrieval has become a major research area due to increasing rate at which images are generated in many application. This paper addresses an important problems related to the content-based images retrieval. It concerns the vector representation of images and its proper use in image retrieval. Indeed, we propose a new model of content-based image retrieval allowing to integrate theories of neural network on a vector space model, where each low level query can be transformed into a score vector. Preliminary results obtained show that our proposed model is effective in a comparative study on two dataset Corel and Caltech-UCSD.","PeriodicalId":412749,"journal":{"name":"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2014.7073271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

Visual information retrieval has become a major research area due to increasing rate at which images are generated in many application. This paper addresses an important problems related to the content-based images retrieval. It concerns the vector representation of images and its proper use in image retrieval. Indeed, we propose a new model of content-based image retrieval allowing to integrate theories of neural network on a vector space model, where each low level query can be transformed into a score vector. Preliminary results obtained show that our proposed model is effective in a comparative study on two dataset Corel and Caltech-UCSD.
基于内容的神经网络图像检索系统
由于在许多应用中图像的生成速度越来越快,视觉信息检索已成为一个重要的研究领域。本文研究了基于内容的图像检索中的一个重要问题。它涉及图像的向量表示及其在图像检索中的正确使用。事实上,我们提出了一种新的基于内容的图像检索模型,允许在向量空间模型上集成神经网络理论,其中每个低级查询可以转换为分数向量。在Corel和Caltech-UCSD两个数据集的对比研究中,初步结果表明我们提出的模型是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信