engleski

Traffic Signs Recognition using Machine Learning

Traffic sign detection and recognition are one of the most popular topics of computer vision and image processing in recent years, as they play an important role in autonomous driving and traffic safety. A great variety of traffic signs are hard to be detected or classified especially if they are spoiled or the driving environment is complicated. In this thesis, the state-of-the-art methods for developing such a recognizer based on machine learning algorithms, are elaborated and discussed. The aim is to design and implement a recognizer that is able to detect and classify different types of traffic signs from images.

computer vision ; classification ; convolutional neural network ; machine learning

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