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-ep.417812019-04-12T05:26:22Z A Real Time Visual Monitoring Module For Traffic Conditions Based On A Modified Auto-Associative Memory 2012-04 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 http://eprints.usm.my/41781/ http://eprints.usm.my/41781/1/EMAD_ISSA_ABDUL_KAREEM.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer |
| institution |
Universiti Sains Malaysia |
| collection |
USM Institutional Repository |
| language |
English |
| topic |
QA75.5-76.95 Electronic computers Computer science |
| spellingShingle |
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 |
| description |
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 |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| 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 |
| granting_institution |
Universiti Sains Malaysia |
| granting_department |
Pusat Pengajian Sains Komputer |
| publishDate |
2012 |
| url |
http://eprints.usm.my/41781/1/EMAD_ISSA_ABDUL_KAREEM.pdf |
| _version_ |
1747820968865169408 |