Computational Intelligence in Visual Sensor Networks: Improving Video Processing Systems

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dc.contributor.author Patricio, MA
dc.contributor.author Castanedo, F
dc.contributor.author Berlanga, A
dc.contributor.author Concha, OP
dc.contributor.author Garcia, J
dc.contributor.author Molina, JM
dc.contributor.editor Hassanien, AE
dc.contributor.editor Abraham, A
dc.contributor.editor Kacprzyk, J
dc.date.accessioned 2011-02-07T06:17:25Z
dc.date.issued 2008-01
dc.identifier.citation Computational Intelligence in Multimedia Processing: Recent Advances, 2008, 1, pp. 351 - 377
dc.identifier.isbn 978-3-540-76826-5
dc.identifier.other B1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/12973
dc.description.abstract In this chapter we will describe several approaches to develop video analysis and segmentation systems based on visual sensor networks using computational intelligence. We review the types of problems and algorithms used, and how computational intelligence paradigms can help to build competitive solutions. computational intelligence is used here from an âengineeringâ point of view: the designer is provided with tools which can help in designing or refining solutions to cope with real-world problems. This implies having an âa prioriâ knowledge of the domain (always imprecise and incomplete) to be reflected in the design, but without accurate mathematical models to apply. The methods used operate at a higher level of abstraction to include the domain knowledge, usually complemented with sets of pre-compiled examples and evaluation metrics to carry out an âinductiveâ generalization process.
dc.publisher Springer
dc.relation.isbasedon 10.1007/978-3-540-76827-2_14
dc.title Computational Intelligence in Visual Sensor Networks: Improving Video Processing Systems
dc.type Chapter
dc.parent Computational Intelligence in Multimedia Processing: Recent Advances
dc.journal.number en_US
dc.publocation Germany en_US
dc.publocation Germany
dc.publocation Germany
dc.publocation Germany
dc.publocation Germany
dc.identifier.startpage 351 en_US
dc.identifier.endpage 377 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 104828
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition 1 en_US
dc.edition 1
dc.edition 1
dc.edition 1
dc.edition 1
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords 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/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems


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