However, with the further advancement and development of Intelligent Transportation Systems (ITS) technology, there is a greater requirement for developing effective and reliable techniques for the improvement of road safety and the assistance of drivers. A significant aspect in this direction is the development of Traffic Sign Recognition (TSR) technology, where a system is required for the identification of different signs on the road, such as warning signs, information signs, and regulation signs. This research is based on the development of a computer vision system, which is required for the elimination of errors arising from driver fatigue, a major cause of traffic accidents. The system is based on the improvement and refinement of Convolutional Neural Networks (CNNs) in such a manner that it is capable of balancing high accuracy with the requirement for information processing in a rapid manner. A high degree of training is provided to the system, enabling it to perform well in different locations. Ultimately, a computerized TSR system is required for the further advancement and development of self-driving cars, creating a well-ordered traffic environment.
Traffic Sign Recognition, Computer Vision, Convolutional Neural Networks, Deep Learning, Intelligent Transportation Systems, Autonomous Vehicles, Image Processing, Road Safety.
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