Abstract
Over the past few decades, advanced technologies have increased the number of vehicles, including cars and motorcycles. Because of the large increase of vehicles, the traffic flow becomes more complex and the traffic accidents increase as rapidly. To decrease the number of traffic accidents, a number of studies has been made for how to manage the traffic flow. Especially for motorcycles, in this paper, we propose a method that counts the motorcycles by Convolutional Neural Network (CNN). To reveal the effectiveness of the proposed method, a set of experiments were conducted and the experimental results show the proposed method can bring out a good performance that provides a good support for traffic management systems.
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Hong, TP., Yang, YC., Su, JH., Chen, CH. (2019). Content-Based Motorcycle Counting for Traffic Management by Image Recognition. In: Nguyen, N., Gaol, F., Hong, TP., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2019. Lecture Notes in Computer Science(), vol 11432. Springer, Cham. https://doi.org/10.1007/978-3-030-14802-7_16
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DOI: https://doi.org/10.1007/978-3-030-14802-7_16
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