Rapidly Adapting Machine Vision for Automated Vehicle Steering
IEEE Expert: Intelligent Systems and Their Applications
Autonomous Driving Goes Downtown
IEEE Intelligent Systems
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Multi-class pattern classification using neural networks
Pattern Recognition
GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection
IEEE Transactions on Image Processing
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Several complex problems have to be solved in order to build Advanced Driving Assistance Systems. Among them, an important problem is the detection and classification of traffic signs, which can appear at any position within a captured image. This paper describes a system that employs independent modules to classify several prohibition road signs. Combining the predictions made by the set of classifiers, a unique final classification is achieved. To reduce the computational complexity and to achieve a real-time system, a previous input feature selection is performed. Experimental evaluation confirms that using this feature selection allows a significant input data reduction without an important loss of output accuracy.