Intelligent processing techniques for semantic-based image and video retrieval

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dc.contributor.author Tang, J
dc.contributor.author Bian, W
dc.contributor.author Yu, N
dc.contributor.author Zhang, Y
dc.date.accessioned 2014-04-14T02:53:59Z
dc.date.issued 2013-01
dc.identifier.citation Neurocomputing, 2013, 119 (1), pp. 1 - 2
dc.identifier.issn 0925-2312
dc.identifier.other C4 en_US
dc.identifier.uri http://hdl.handle.net/10453/27211
dc.description.abstract Rapid advances in technology for capturing, processing, distributing, storing, and presenting visual data have resulted in a proliferation of image and video data in human lives. The multimedia research community has widely recognized the importance of searching images or videos from a large-scale corpus or the Internet. Intelligent processing techniques are the most useful tools to achieve this objective and the recent years have witnessed very significant contributions of intelligent algorithms in multimedia search. Intelligent information processing, such as machine learning techniques, knowledge discovery and data mining, computer vision and cognitive computation, natural language processing, and intelligent humanmachine interfaces, have great influence on extracting the semantic information for image and video data. These techniques light a way to make the semantic-based image/video retrieval come true. At least, they provide us a reasonable direction to touch the semantic retrieval. The goals of this special issue are three-fold: (1) introduce novel research in intelligent processing techniques for semantic-based image and video retrieval; (2) survey on the progress of this area in the past years; and (3) discuss new applications based on semantic-based image and video retrieval models.
dc.format Scott McWhirter
dc.publisher Elsevier Science Bv
dc.relation.isbasedon 10.1016/j.neucom.2012.11.037
dc.title Intelligent processing techniques for semantic-based image and video retrieval
dc.type Journal Article
dc.parent Neurocomputing
dc.journal.volume 1
dc.journal.volume 119
dc.journal.number 1 en_US
dc.publocation Amsterdam en_US
dc.identifier.startpage 1 en_US
dc.identifier.endpage 2 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 115849
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)
utslib.collection.history Uncategorised (ID: 363)


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