A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory
A new trend of traffic light monitoring module is the module that uses real time visual data and a computer vision approach to reflect the traffic conditions (crowded, normal and empty). This approach determines the traffic conditions by counting the number of vehicles individually on the street wit...
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2012
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my.usm.eprints.41781 http://eprints.usm.my/41781/ A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory Kareem, Emad Issa Abdul QA75.5-76.95 Electronic computers. Computer science A new trend of traffic light monitoring module is the module that uses real time visual data and a computer vision approach to reflect the traffic conditions (crowded, normal and empty). This approach determines the traffic conditions by counting the number of vehicles individually on the street with the use of complex techniques. However this gives rise to some limitations. These limitations can be tackled when a multitude of vehicles in the street is detected as a group rather than individually. Such a technique can be achieved by using the auto-associative memory. 2012-04 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/41781/1/EMAD_ISSA_ABDUL_KAREEM.pdf Kareem, Emad Issa Abdul (2012) A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory. PhD thesis, Universiti Sains Malaysia. |
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QA75.5-76.95 Electronic computers. Computer science Kareem, Emad Issa Abdul A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory |
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A new trend of traffic light monitoring module is the module that uses real time visual data and a computer vision approach to reflect the traffic conditions (crowded, normal and empty). This approach determines the traffic conditions by counting the number of vehicles individually on the street with the use of complex techniques. However this gives rise to some limitations. These limitations can be tackled when a multitude of vehicles in the street is detected as a group rather than individually. Such a technique can be achieved by using the auto-associative memory. |
format |
Thesis |
author |
Kareem, Emad Issa Abdul |
author_facet |
Kareem, Emad Issa Abdul |
author_sort |
Kareem, Emad Issa Abdul |
title |
A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory |
title_short |
A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory |
title_full |
A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory |
title_fullStr |
A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory |
title_full_unstemmed |
A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory |
title_sort |
real time visual monitoring module for traffic conditions based on a modified auto-associative memory |
publishDate |
2012 |
url |
http://eprints.usm.my/41781/1/EMAD_ISSA_ABDUL_KAREEM.pdf http://eprints.usm.my/41781/ |
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1643710319700213760 |
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13.18916 |