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Reduced computational cost prototype for street theft detection based on depth decrement in Convolutional Neural Network. Application to Command and Control Information Systems (C2IS) in the National Police of Colombia

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Reduced computational cost prototype for street theft detection based on depth decrement in Convolutional Neural Network. Application to Command and Control Information Systems (C2IS) in the National Police of Colombia

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Suarez-Paez, JE.; Salcedo-González, ML.; Esteve Domingo, M.; Gomez, J.; Palau Salvador, CE.; Pérez Llopis, I. (2018). Reduced computational cost prototype for street theft detection based on depth decrement in Convolutional Neural Network. Application to Command and Control Information Systems (C2IS) in the National Police of Colombia. International Journal of Computational Intelligence Systems. 12(1):123-130. https://doi.org/10.2991/ijcis.2018.25905186

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/123473

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Title: Reduced computational cost prototype for street theft detection based on depth decrement in Convolutional Neural Network. Application to Command and Control Information Systems (C2IS) in the National Police of Colombia
Author: Suarez-Paez, Julio Ernesto Salcedo-González, Mayra Liliana Esteve Domingo, Manuel Gomez, J.A. Palau Salvador, Carlos Enrique Pérez Llopis, Israel
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Issued date:
Abstract:
[EN] This paper shows the implementation of a prototype of street theft detector using the deep learning technique R- CNN (Region-Based Convolutional Network), applied in the Command and Control Information System (C2IS) ...[+]
Subjects: Deep Learning , R-CNN , AlexNet , VGG16 , VGG19 , CNN (Convolutional Neural Network) , Command and Control Information System (C2IS)
Copyrigths: Reconocimiento - No comercial (by-nc)
Source:
International Journal of Computational Intelligence Systems. (issn: 1875-6883 )
DOI: 10.2991/ijcis.2018.25905186
Publisher:
Atlantis Press
Publisher version: http://doi.org/10.2991/ijcis.2018.25905186
Type: Artículo

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