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Auditory Classification of Vehicles for Scene Understanding

Scott Kaghaz-Garan-2013-12-01-Academic Commons (Stony Brook University)
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TL;DRAbstract

There have been numerous studies on the classification of auditory signals. In contrast,there have been very few studies in the implementation and classification of vehicles using purely auditory signals. This thesis presents an implementation of auditory vehicle identification using support vector machines. It explores how granular classification can be, from what type of vehicle to what action the vehicle is preforming. The granularity of the classification will greatly aid in auditory scene understanding. The classifications are done with computational complexity in mind, so embedded systems can utilize the findings. A simple averaging algorithm will also be explored that aids in classification significantly. | 44 pages

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There have been numerous studies on the classification of auditory signals. In contrast,there have been very few studies in the implementation and classification of vehicles using purely auditory signals. This thesis presents an implementation of auditory vehicle identification using support vector machines. It explores how granular classification can be, from what type of vehicle to what action the vehicle is preforming. The granularity of the classification will greatly aid in auditory scene understanding. The classifications are done with computational complexity in mind, so embedded systems can utilize the findings. A simple averaging algorithm will also be explored that aids in classification significantly. | 44 pages

Keywords

Computer scienceArtificial intelligenceGeography

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