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In this study, we have designed a vehicle classification system which classifies Assault Amphibian Vehicle and Dragon Wagon, using acoustic and sesimic features. We implemented Mel Frequency Cepstral Coefficient (MFCC) algorithm to extract features of the acoustic and sesimic data, and these extracted features were reduced by using Vector Quantizaton algorithm. Both Support Vector Machine (SVM) and...
Classification of ground vehicles based on acoustic signals can be employed effectively in battlefield surveillance, traffic control, and many other applications. The classification performance depends on the selection of signal features that determine the separation of different signal classes. In this paper, we investigate two feature extraction methods for acoustic signals from moving ground vehicles...
There are important significance and social benefit of the application for real-time classification by using of the combination of GA, PCA and Improved SVM in a road ramp. The eight test points were put on the both sides of the road ramp, extracted feature vectors. The acoustic and seismic signals were used to research the classification in real-time. Because the dimension of feature vectors is too...
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