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dc.contributor.convenorNaveen Sharma
dc.contributor.authorBlumenstein, Michael
dc.date.accessioned2017-05-03T12:05:48Z
dc.date.available2017-05-03T12:05:48Z
dc.date.issued2010
dc.date.modified2012-09-17T22:00:09Z
dc.identifier.urihttp://hdl.handle.net/10072/39124
dc.description.abstractThe quest to develop artificially intelligent machines that exhibit the behaviour of their biological counterparts has yielded decades of inspired investigation. Recently, a number of significant outcomes have been proffered in the domain of "Artificial Intelligence" research, however despite tremendous progress in the field, a number of challenges still remain. These include the inherent difficulties in replicating the biological complexities of the human brain, but also relate to the practical problems of having rapid and convenient access to real-world data, the ability to effectively manipulate, process and classify unknown records, as well as the efficient management of large quantities of categorised information. This presentation explores the groundbreaking developments in the areas of computer vision, automated pattern recognition and artificial intelligence in the context of real-world problems that are underpinned by the need to apply large volumes of accurate data for training and processing. A number of applications are presented including research into intelligent on-line water quality monitoring technology to ensure sustainable, safe supplies of freshwater across large-scale networks, in addition to the development of automatic systems for monitoring the activities of visitors at our beaches and coastal zones, as well as technologies for preventing the deterioration and collapse of bridges, and finally software that can be used for the early diagnosis and treatment of such brain disorders as Parkinson's disease. Further discussion is dedicated to the future data and resource requirements of artificial intelligence research, implications of the National Broadband Network roll-out, and finally possible directions for attaining the goal of conscious machines.
dc.description.publicationstatusYes
dc.format.extent52860 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherNo data provided
dc.publisher.urihttp://archive.questnet.edu.au/display/qnc2010/
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameQUESTnet 2010
dc.relation.ispartofconferencetitleQUESTnet 2010
dc.relation.ispartofdatefrom2010-07-06
dc.relation.ispartofdateto2010-07-09
dc.relation.ispartoflocationGold Coast, Australia
dc.rights.retentionN
dc.subject.fieldofresearchNetworking and Communications
dc.subject.fieldofresearchcode080503
dc.titleThe data connection - challenges at the frontiers of Artificial Intelligence research
dc.typeConference output
dc.type.descriptionE3 - Conferences (Extract Paper)
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© The Author(s) 2010. This is the author-manuscript version of this paper. It is posted here with permission of the copyright owner for your personal use only. No further distribution permitted. For information about this conference please refer to the conference’s website or contact the author.
gro.date.issued2010
gro.hasfulltextFull Text
gro.griffith.authorBlumenstein, Michael M.


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    Contains papers delivered by Griffith authors at national and international conferences.

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