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AuthorChen S.
AuthorSong B.
AuthorFan L.
AuthorDu X.
AuthorGuizani M.
Available date2020-03-18T10:47:15Z
Publication Date2019
Publication NameIEEE Transactions on Cognitive Communications and Networking
ResourceScopus
ISSN23327731
URIhttp://dx.doi.org/10.1109/TCCN.2019.2893360
URIhttp://hdl.handle.net/10576/13410
AbstractDue to spectrum scarcity and energy consumption caused by processing and transmitting multimodal data signals in cognitive radio networks (CRNs), locating key information in the signal for further energy management in EH CRNs is necessary. Therefore, to adaptively capture semantic associations of multimedia signals, we present a novel visual-semantic reasoning framework for phrases simultaneously localization. To address the preferences limitations of current algorithms caused by the independent localizing of phrases and the ignorance of inter-phrase dependencies, our framework models the phrases simultaneously followed by inter-phrase dependencies-based jointly localization. Specifically, the framework consists of two core modules, including spatial-semantic perception tensor factorization and visual-semantic relationship reasoning network which can be denoted as SSPTF and VSRN, respectively. That is, SSPTF integrates regions and phrases into a tensor so that tensor factorization can be used to capture a shared potential association for all phrases. Furthermore, based on the predefined phrases-semantic dependencies graph, VSRN explicitly exploits the conjunctions between phrases to refine the phrase-region matching scores from SSPTF to achieve jointly localization. By constructing it as an end-to-end training architecture, the strong performance of the framework over Flicker-Entities30K on accuracy and the state-of-the-art results on some categories demonstrate the effectiveness of the proposed unified framework.
SponsorThis work was supported by the National Natural Science Foundation of China under Grant (No. 61772387 and No. 61802296), Fundamental Research Funds of Ministry of Education and China Mobile (MCM20170202), China Postdoctoral Science Foundation Grant (No. 2017M620438)
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectMulti-media signals processing
phrase simultaneously localization
spatial-semantic perception tensor factorization
unified phrase localization framework
visual-semantic reasoning
TitleMulti-modal data semantic localization with relationship dependencies for efficient signal processing in EH CRNs
TypeConference Paper
Pagination347-357
Issue Number2
Volume Number5
dc.accessType Abstract Only


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