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dc.contributor.convenorNaveen Sharmaen_US
dc.contributor.authorBlumenstein, Michaelen_US
dc.date.accessioned2017-05-03T12:05:48Z
dc.date.available2017-05-03T12:05:48Z
dc.date.issued2010en_US
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.en_US
dc.description.publicationstatusYesen_US
dc.format.extent52860 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherNo data provideden_US
dc.publisher.urihttps://www.questnet.edu.au/display/qnc2010/Homeen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofconferencenameQUESTnet 2010en_US
dc.relation.ispartofconferencetitleQUESTnet 2010en_US
dc.relation.ispartofdatefrom2010-07-06en_US
dc.relation.ispartofdateto2010-07-09en_US
dc.relation.ispartoflocationGold Coast, Australiaen_US
dc.rights.retentionNen_US
dc.subject.fieldofresearchNetworking and Communicationsen_US
dc.subject.fieldofresearchcode080503en_US
dc.titleThe data connection - challenges at the frontiers of Artificial Intelligence researchen_US
dc.typeConference outputen_US
dc.type.descriptionE3 - Conference Publications (Extract Paper)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.rights.copyrightCopyright remains with the author 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.en_US
gro.date.issued2010
gro.hasfulltextFull Text


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

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