Application of deep learning in image processing of unmanned vehicles

Abstract

Artificial Intelligence has accelerated research on autonomous vehicles in the past few years. However, it is not easy to achieve full autonomy on account of the essence of a complex and dynamic driving environment. Fortunately, the rapid development of deep learning has made great progress, which can be used to solve problems about image processing in the autonomous vehicles field. This paper offers a comprehensive review of the recent deep-learning-based image processing methods that leverage data detected. The paper gives a brief overview of deep learning, discussing basic concepts and principles. We also discuss the common models and architectures of deep learning and introduce typical deep learning techniques: convolutional neural networks (CNN). Furthermore, we divided the application of deep learning in the autonomous vehicles into three parts and discuss them respectively. Finally, we review the disadvantages of the application of deep learning in image processing for autonomous vehicles. On this basis, we put forward our insights and point out promising research directions.