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.
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 CN...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2018-11-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/25905186/view |
| _version_ | 1818043633196072960 |
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| author | Julio Suarez-Paez Mayra Salcedo-Gonzalez M. Esteve J.A. Gómez C. Palau I. Pérez-Llopis |
| author_facet | Julio Suarez-Paez Mayra Salcedo-Gonzalez M. Esteve J.A. Gómez C. Palau I. Pérez-Llopis |
| author_sort | Julio Suarez-Paez |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T09:05:19Z |
| format | Article |
| id | doaj.art-67c525463b52415b9c3ca44de59607ae |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-12-10T09:05:19Z |
| publishDate | 2018-11-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-67c525463b52415b9c3ca44de59607ae2022-12-22T01:55:10ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832018-11-0112110.2991/ijcis.2018.25905186Reduced 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.Julio Suarez-PaezMayra Salcedo-GonzalezM. EsteveJ.A. GómezC. PalauI. Pérez-LlopisThis 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.https://www.atlantis-press.com/article/25905186/viewDeep LearningR-CNNAlexNetVGG16VGG19CNN (Convolutional Neural Network) |
| spellingShingle | Julio Suarez-Paez Mayra Salcedo-Gonzalez M. Esteve J.A. Gómez C. Palau I. Pérez-Llopis 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 Deep Learning R-CNN AlexNet VGG16 VGG19 CNN (Convolutional Neural Network) |
| 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. |
| title_full | 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. |
| title_fullStr | 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. |
| title_full_unstemmed | 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. |
| title_short | 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. |
| title_sort | 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 |
| topic | Deep Learning R-CNN AlexNet VGG16 VGG19 CNN (Convolutional Neural Network) |
| url | https://www.atlantis-press.com/article/25905186/view |
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