Abstract
The detection of the degree of congestion in the carriage is based on the evaluation of the number of passengers in the carriage. The target detection algorithm based on the deep neural network can accurately identify the number of passengers in the carriage and evaluate the degree of congestion in the carriage. This paper conducts related researches on the functions and uses of image recognition in an intelligent train service system in a subway train, including congestion detection research based on image recognition, passenger abnormal behavior analysis research based on image recognition, and driver fatigue based on image recognition The three pieces of content were detected and related principle analysis was carried out. This article expounds the principles of the above three pieces of content, and provides a certain research foundation for subsequent research in this field.
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Acknowledgements
This work was supported by National Key R&D Program of China (2016YFB1200402).
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Zhang, J., Li, Y., Huo, M. (2021). Relevant Research on Image Recognition Content in the Intelligent Train Service System of a Subway Train. In: Chen, W., Yang, Q., Wang, L., Liu, D., Han, X., Meng, G. (eds) The Proceedings of the 9th Frontier Academic Forum of Electrical Engineering. Lecture Notes in Electrical Engineering, vol 743. Springer, Singapore. https://doi.org/10.1007/978-981-33-6609-1_16
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DOI: https://doi.org/10.1007/978-981-33-6609-1_16
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