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14 November 2001 Support vector machine application on vehicles
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Abstract
In this paper, methods of choosing a vehicle out of an image are explored. Digital images are taken from a monocular camera. Image processing techniques are applied to each single frame picture to create the feature vector. Finally the resulting features are used to classify whether there is a car in the picture or not using support vector machines. The results are compared to those obtained using a neural network. A discussion on techniques to enhance the feature vector and the results from both learning machines will be included.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Del Rose and Jack Reed "Support vector machine application on vehicles", Proc. SPIE 4479, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation IV, (14 November 2001); https://doi.org/10.1117/12.448342
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