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dc.contributor.authorAchkar, Rogeren_US
dc.contributor.authorNarcis , Johnnyen_US
dc.contributor.authorAbou Awad, Waelen_US
dc.contributor.authorHitti, Karimen_US
dc.description.abstractObject detection and classification in Artificial Neural Networks (ANN) can play an important part in finding solutions for various tasks that are considered critical or time consuming if executed by humans. Also, object detection can be used in several applications and domains. One of which is physical security, where many illegal items, that should not pass through checkpoints, exist. In this sense, smart X-ray scanners can help in detecting any restricted object like weapons, knives or even drugs within a bag or held by an individual. This paper aims to provide a first step towards smart scanners where the MultiLayer Perceptron (MLP) is used to classify and detect two different types of illegal objects. Moreover, training of the network is performed using the Back Propagation algorithm, one of the most widely used algorithms in the MLP.en_US
dc.subjectComputational modelingen_US
dc.subjectMathematical modelen_US
dc.subjectArtificial neural networksen_US
dc.titleSmart x-ray scanners using artificial neural networksen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Computer Modelling and Simulation (20th : 27-29 March 2018 : Cambrige, UK)en_US
dc.contributor.affiliationDepartment of Mathematicsen_US
dc.relation.ispartoftext2018 UKSim-AMSS 20th International Conference on Computer Modelling and Simulation (UKSim)en_US
dc.provenance.recordsourceOliben_US of Arts and Sciences-
Appears in Collections:Department of Mathematics
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