Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/1342
Title: Smart x-ray scanners using artificial neural networks
Authors: Achkar, Roger
Narcis , Johnny
Abou Awad, Wael
Hitti, Karim 
Affiliations: Department of Mathematics 
Keywords: Computational modeling
Mathematical model
Artificial neural networks
Issue Date: 2018
Part of: 2018 UKSim-AMSS 20th International Conference on Computer Modelling and Simulation (UKSim)
Conference: International Conference on Computer Modelling and Simulation (20th : 27-29 March 2018 : Cambrige, UK) 
Abstract: 
Object 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.
URI: https://scholarhub.balamand.edu.lb/handle/uob/1342
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Mathematics

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