Smart object counter
Vehicle counting is made possible with the help many advanced computer vision algorithms. This project will be investigating many computer visions models especially destiny map estimation approach such as CSRNet, DMCount, M-SFANet+M-SegNet and etc. after evaluations will be conducted to determine th...
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Nanyang Technological University
2021
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sg-ntu-dr.10356-1480992021-04-23T13:18:26Z Smart object counter Wong, Chun Foong Loke Yuan Ren School of Computer Science and Engineering yrloke@ntu.edu.sg Engineering::Computer science and engineering Vehicle counting is made possible with the help many advanced computer vision algorithms. This project will be investigating many computer visions models especially destiny map estimation approach such as CSRNet, DMCount, M-SFANet+M-SegNet and etc. after evaluations will be conducted to determine the best approach in vehicle counting. After which, the best models will be implemented into a web-based application that will perform vehicle counts. ReactJS will be used to create a front-end website to display essential data. Next NodeJs and FlaskJs will be used to create back end so that data can be processed before routing it back the front end for display purposes and analysis can be conducted as well. Overall, the objective of the project is finding the best approach to conduct vehicle counting and results are fairly accurate in term of estimation. Bachelor of Engineering (Computer Science) 2021-04-23T13:18:25Z 2021-04-23T13:18:25Z 2021 Final Year Project (FYP) Wong, C. F. (2021). Smart object counter. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148099 https://hdl.handle.net/10356/148099 en application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering Wong, Chun Foong Smart object counter |
description |
Vehicle counting is made possible with the help many advanced computer vision algorithms. This project will be investigating many computer visions models especially destiny map estimation approach such as CSRNet, DMCount, M-SFANet+M-SegNet and etc. after evaluations will be conducted to determine the best approach in vehicle counting.
After which, the best models will be implemented into a web-based application that will perform vehicle counts.
ReactJS will be used to create a front-end website to display essential data. Next NodeJs and FlaskJs will be used to create back end so that data can be processed before routing it back the front end for display purposes and analysis can be conducted as well.
Overall, the objective of the project is finding the best approach to conduct vehicle counting and results are fairly accurate in term of estimation. |
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Loke Yuan Ren |
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Loke Yuan Ren Wong, Chun Foong |
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Final Year Project |
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Wong, Chun Foong |
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Wong, Chun Foong |
title |
Smart object counter |
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Smart object counter |
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Smart object counter |
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Smart object counter |
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Smart object counter |
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smart object counter |
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Nanyang Technological University |
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2021 |
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https://hdl.handle.net/10356/148099 |
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