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Binary Image Classification Using Convolutional Neural Network for V2V Communication Systems

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Part of the Studies in Computational Intelligence book series (SCI,volume 1045)

Abstract

This research presents a method based on deep learning network architecture for image classification problems for a communication system between autonomous vehicles. Vehicular communication is a research direction of data transmission between autonomous vehicles based on a communication system called a vehicular optical communication camera (VOCC). Thanks to the VOCC system, the vehicles transfer information about the position, direction, speed, and future behavior. In addition, the power of the deep learning network-based proposed algorithm improves the VOCC system to gain the accuracy of image processing from the acquisition of signals from autonomous vehicles. Experimental results show that the proposed algorithm achieves high performance on image signals with difficult conditions.

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Correspondence to Dao N. Ngoc .

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Vo, HT., Nguyen, NL., Ngoc, D.N., Do, TH., Pham, QD. (2023). Binary Image Classification Using Convolutional Neural Network for V2V Communication Systems. In: Phuong, N.H., Kreinovich, V. (eds) Biomedical and Other Applications of Soft Computing. Studies in Computational Intelligence, vol 1045. Springer, Cham. https://doi.org/10.1007/978-3-031-08580-2_10

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