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

doi:10.1007/s11042-018-6043-0

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能感知与计算研究中心

	Deep-MATEM: TEM query image based cross-modal retrieval for material science literature
	Li, Hailiang 1,2; Guan, Qingxiao 2,3; Wang, Haidong 1; Dong, Jing2,4
刊名	MULTIMEDIA TOOLS AND APPLICATIONS
	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
DOI	10.1007/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).
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关键词	SCALE ; CLASSIFICATION ; FEATURES
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000448401600006
资助机构	National Natural Science Foundation of China ; National Key Research and Development Program of China
内容类型	期刊论文
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.