Vol. 3 No. 1 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

Deep Learning for Autonomous Vehicle Image and Video Processing

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  • Dr. Andrei Tonkoshkur
Dr. Andrei Tonkoshkur
Associate Professor of Computer Science, Belarusian State University of Informatics and Radioelectronics (BSUIR)
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Published 14-05-2023

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Andrei Tonkoshkur, “Deep Learning for Autonomous Vehicle Image and Video Processing”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 1, pp. 311–342, May 2023, Accessed: Sep. 19, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/85

Abstract

Autonomous vehicles have garnered increasing attention due to advancements in deep learning algorithms [1]. Vision-based driving assistance often uses computational architectures like recurrent neural networks due to the low cost of cameras. However, self-driving car systems requiring the low-latency operation benefit from well-optimized software and hardware stacks. Further, the training process of deep learning models is computationally expensive, often taking days, or even weeks, to finish [2]. Deep learning is setting new benchmarks in various fields almost daily.

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