Abstract
Traffic flow classification is an integrated task of traffic management and network mobility. In this work, a feature collection system is developed to collect the moving and appearance-based features of traffic images, and their performance are evaluated by different machine learning techniques including Deep Neural Networks (DNN), and Convolutional Neural Networks (CNN). The experimental results for a challenging highway video with three traffic flow classes of light, medium and heavy indicates the highest performance of CNN with \(90\%\) accuracy.
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Shirazi, M.S., Morris, B. (2018). Traffic Flow Classification Using Traffic Cameras. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2018. Lecture Notes in Computer Science(), vol 11241. Springer, Cham. https://doi.org/10.1007/978-3-030-03801-4_66
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DOI: https://doi.org/10.1007/978-3-030-03801-4_66
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