Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions

The paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digi...

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Main Authors: Slobodan Beroš, Saša Mladenović, Špiro Matošin
Format: Article
Language:English
Published: University of Zagreb, Faculty of Transport and Traffic Sciences 2012-10-01
Series:Promet (Zagreb)
Online Access:http://www.fpz.unizg.hr/traffic/index.php/PROMTT/article/view/786
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spelling doaj-72535ff13bf642cf977b32f27201467c2020-11-25T02:43:26ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692012-10-019311312010.7307/ptt.v9i3.786643Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific ConditionsSlobodan BerošSaša MladenovićŠpiro MatošinThe paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digitalcircuits as crucial in real-time applications is pointed out. Thesimulation based on the use of reduced high level noise pictureand a tree 2. 7. software have shown excellent results. The consideredand simulated adaptive neural network based systemwith its good recognition and convergence is a useful real-timesolution for vehicle recognition and count in the floating bridgesevere conditions.http://www.fpz.unizg.hr/traffic/index.php/PROMTT/article/view/786
collection DOAJ
language English
format Article
sources DOAJ
author Slobodan Beroš
Saša Mladenović
Špiro Matošin
spellingShingle Slobodan Beroš
Saša Mladenović
Špiro Matošin
Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions
Promet (Zagreb)
author_facet Slobodan Beroš
Saša Mladenović
Špiro Matošin
author_sort Slobodan Beroš
title Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions
title_short Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions
title_full Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions
title_fullStr Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions
title_full_unstemmed Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions
title_sort neuro system structure for vehicle recognition and count in floating bridge specific conditions
publisher University of Zagreb, Faculty of Transport and Traffic Sciences
series Promet (Zagreb)
issn 0353-5320
1848-4069
publishDate 2012-10-01
description The paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digitalcircuits as crucial in real-time applications is pointed out. Thesimulation based on the use of reduced high level noise pictureand a tree 2. 7. software have shown excellent results. The consideredand simulated adaptive neural network based systemwith its good recognition and convergence is a useful real-timesolution for vehicle recognition and count in the floating bridgesevere conditions.
url http://www.fpz.unizg.hr/traffic/index.php/PROMTT/article/view/786
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AT sasamladenovic neurosystemstructureforvehiclerecognitionandcountinfloatingbridgespecificconditions
AT spiromatosin neurosystemstructureforvehiclerecognitionandcountinfloatingbridgespecificconditions
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