International Journal of Computational Intelligence Systems

Volume 12, Issue 1, November 2018, Pages 123 - 130

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.

Authors
Julio Suarez-Paez1, juliosuarez@ieee.org, Mayra Salcedo-Gonzalez1, m.l.salcedogonzalez@ieee.org, M. Esteve1, mesteve@dcom.upv.es, J.A. Gómez2, jon@dsic.upv.es, C. Palau1, cpalau@dcom.upv.es, I. Pérez-Llopis1, ispello0@upvnet.upv.es
1Distributed Real-time Systems Laboratory (SATRD), Universitat Politècnica de València, Camino de Vera, s/n Valencia, 46022, Spain
2Pattern Recognition and Human Language Technology, Universitat Politècnica de València, Camino de Vera, s/n Valencia, 46022, Spain
Received 7 April 2018, Accepted 16 September 2018, Available Online 1 November 2018.
DOI
https://doi.org/10.2991/ijcis.2018.25905186How to use a DOI?
Keywords
Deep Learning, R-CNN, AlexNet, VGG16, VGG19, CNN (Convolutional Neural Network), Command and Control Information System (C2IS)
Abstract

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) of National Police of Colombia, the prototype is implemented using three models of CNN (Convolutional Neural Network), AlexNet, VGG16 and VGG19 comparing their computational cost measuring the image processing time, according to the complexity (depth) of each model. Finally, we conclude which model has the lowest computational cost and is more useful for the case of the National Police of Colombia.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
12 - 1
Pages
123 - 130
Publication Date
2018/11
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.2018.25905186How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Julio Suarez-Paez
AU  - Mayra Salcedo-Gonzalez
AU  - M. Esteve
AU  - J.A. Gómez
AU  - C. Palau
AU  - I. Pérez-Llopis
PY  - 2018
DA  - 2018/11
TI  - 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.
JO  - International Journal of Computational Intelligence Systems
SP  - 123
EP  - 130
VL  - 12
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2018.25905186
DO  - https://doi.org/10.2991/ijcis.2018.25905186
ID  - Suarez-Paez2018
ER  -