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Deep-MATEM: TEM query image based cross-modal retrieval for material science literature

文献类型：期刊论文

作者Li, Hailiang1,2; Guan, Qingxiao2,3; Wang, Haidong1; Dong, Jing2,4
刊名MULTIMEDIA TOOLS AND APPLICATIONS
出版日期2018-12-01
卷号77期号:23页码:30269-30290
关键词Cross-Modal Document retrieval Convolutional network Material science
ISSN号1380-7501
DOI10.1007/s11042-018-6043-0
通讯作者Guan, Qingxiao(258817567@qq.com)
英文摘要With the rapid increasing of published material science literatures, an effective literature retrieving system is important for researchers to obtain relevant information. In this paper we propose a cross-modal material science literatures retrieval method using transmission electron microscopy(TEM) image as query information, which provide a access of using material experiment generated TEM image data to retrieve literatures. In this method, terminologies are extracted and topic distribution are inferred from text part of literatures by using LDA, and we design a multi-task Convolutional Neuron Network(CNN) mapping query TEM image to the relevant terminologies and topic distribution predictions. The ranking score is calculated from output for query image and text data. Experimental results shows our method achieves better performance than multi-label CCA, Deep Semantic Matching(Deep SM) and Modality-Specific Deep Structure(MSDS).
WOS关键词SCALE ; CLASSIFICATION ; FEATURES
资助项目National Natural Science Foundation of China[U1536105] ; National Natural Science Foundation of China[51474237] ; National Natural Science Foundation of China[U1536120] ; National Natural Science Foundation of China[U1636201] ; National Key Research and Development Program of China[2016YFB1001003]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000448401600006
出版者SPRINGER
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China
源URL[http://ir.ia.ac.cn/handle/173211/22827]  
专题自动化研究所_智能感知与计算研究中心
通讯作者Guan, Qingxiao
作者单位1.Cent S Univ, Sch Minerals Proc & Bioengn, Changsha 410083, Hunan, Peoples R China
2.Chinese Acad Sci, Inst Informat Engn, State Key Lab Informat Secur, Beijing 100093, Peoples R China
3.Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 100093, Peoples R China
4.Chinese Acad Sci, Inst Automat, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Li, Hailiang,Guan, Qingxiao,Wang, Haidong,et al. Deep-MATEM: TEM query image based cross-modal retrieval for material science literature[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2018,77(23):30269-30290.
APA Li, Hailiang,Guan, Qingxiao,Wang, Haidong,&Dong, Jing.(2018).Deep-MATEM: TEM query image based cross-modal retrieval for material science literature.MULTIMEDIA TOOLS AND APPLICATIONS,77(23),30269-30290.
MLA Li, Hailiang,et al."Deep-MATEM: TEM query image based cross-modal retrieval for material science literature".MULTIMEDIA TOOLS AND APPLICATIONS 77.23(2018):30269-30290.

入库方式： OAI收割

来源：自动化研究所

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