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Code for Vehicle Classification based on Image and Sound

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17

Description

By extracting the Mel-frequency cepstral coefficients of the sound signature of a vehicle, it is possible to classify it. The MATLAB neural network algorithm had a high success rate of correctly classifying a vehicle, while the C++ neural network algorithm needed more information.

With the introduction of an additional feature – the physical size of a vehicle – it was possible to achieve a sufficiently high percentage of accuracy in classifying two vehicle classes based on the acoustic characteristics of a vehicle.

This allowed implementing the framework for a reliable classification system using the acoustic and physical features of vehicles.

https://matlab1.com/classification-2/

https://arxiv.org/ftp/arxiv/papers/1804/1804.01212.pdf

1 review for Code for Vehicle Classification based on Image and Sound

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    Anna

    This project helped me a lot.

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