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dc.contributor.authorRangel, José Carlos
dc.contributor.authorPinzón, Cristian
dc.date.accessioned2020-01-06T14:36:04Z
dc.date.available2020-01-06T14:36:04Z
dc.date.issued01/09/2019
dc.identifierhttps://link.springer.com/chapter/10.1007/978-3-319-99608-0_64
dc.identifier.urihttps://ridda2.utp.ac.pa/handle/123456789/9447
dc.descriptionSurveillance systems are quite common in almost every building. The current dimension of these systems is huge and involves a great deal of hardware and human resources for achieving these objectives. This paper proposes the use of an agent-based architecture for helping in the categorization of the places where these are deployed. Proposal uses a deep learning model for evaluating the images captured by the cameras and then label the zone where the camera is located.en_US
dc.description.abstractSurveillance systems are quite common in almost every building. The current dimension of these systems is huge and involves a great deal of hardware and human resources for achieving these objectives. This paper proposes the use of an agent-based architecture for helping in the categorization of the places where these are deployed. Proposal uses a deep learning model for evaluating the images captured by the cameras and then label the zone where the camera is located.en_US
dc.formatapplication/pdf
dc.language.isoenen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectSoftware-Agentsen_US
dc.subjectSemantic-Categorizationen_US
dc.subjectDeep-Learningen_US
dc.titleMultiagent System for Semantic Categorization of Places Mean the Use of Distributed Surveillance Camerasen_US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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