Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/110246
Title: | Reconocimiento de señales de tráfico |
Author: | González Hidalgo, Antonio |
Director: | Ventura, Carles |
Tutor: | Burguera, Antoni |
Abstract: | This TFM presents a system capable of detecting and classifying traffic signs from static images. The proposed system is based on two neural networks: one for signal detection and one for classification. In the first part, the work is focused on finding the parameters that offer the best accuracy for each of the NNCs. Then, a series of examples are made to check the correct functioning of the CNNs. Each CNN is analyzed separately and finally, an example of the global operation of the system is implemented. |
Keywords: | deep learning Keras neural networks traffic signs signal detection |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2019 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
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agonzalezhidalgoTFM0619memoria.pdf | Memoria del TFM | 17,53 MB | Adobe PDF | View/Open |
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