implement classification for traffic signs using convolutional neural network – Mohamad Abdulrahman
Mohamad Abdulrahman
Master's thesis
implement classification for traffic signs using convolutional neural network
Abstract:
The ability to classify traffic signs quickly and effectively is great importance for autonomous cars or as a driver’s assistance in some difficult circumstances. many techniques in machine learning were used like Support Vector Machine and Random Forest, on the other hand deep learning techniques reached state of art performance in many image classifications tasks. Convolutional neural networks have …more
Language used: English
Date on which the thesis was submitted / produced: 31. 3. 2021
Thesis defence
- Supervisor: doc. Ing. Arnošt Veselý, CSc.
Citation record
ISO 690-compliant citation record:
ABDULRAHMAN, Mohamad. \textit{implement classification for traffic signs using convolutional neural network}. Online. Master's thesis. Praha: Czech University of Life Sciences Prague, Faculty of Economics and Management. 2021. Available from: https://theses.cz/id/u7sb3m/.
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Institution archiving the thesis and making it accessible: Česká zemědělská univerzita v Praze, Provozně ekonomická fakultaCzech University of Life Sciences Prague
Faculty of Economics and ManagementMaster programme / field:
Systems Engineering and Informatics / Informatics
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