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
- 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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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 - 2018/11/01 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 - 10.2991/ijcis.2018.25905186 ID - Suarez-Paez2018 ER -