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

Deep Learning for Autonomous Vehicle Image and Video Processing

Dr. Andrei Tonkoshkur
Associate Professor of Computer Science, Belarusian State University of Informatics and Radioelectronics (BSUIR)
Cover

Published 14-05-2023

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: Nov. 07, 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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