Traffic sign recognition with deep convolutional neural networks

Boris Karamatić (2016) Traffic sign recognition with deep convolutional neural networks. EngD thesis.

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Abstract

The problem of detection and recognition of traffic signs is becoming an important problem when it comes to the development of self driving cars and advanced driver assistance systems. In this thesis we will develop a system for detection and recognition of traffic signs. For the problem of detection we will use aggregate channel features and for the problem of recognition we will use a deep convolutional neural network. We will describe how convolutional neural networks work, how they are constructed and we will explain the use of every layer. We will describe the steps we took to develop our convolutional neural network. We will evaluate the results of detection and classification on established traffic sign datasets.

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