This is a survey of neural network applications in the real-world scenario. It provides a
taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …

Modern cars are incorporating an increasing number of driver assist features, among which
automatic lane kee**. The latter allows the car to properly position itself within the road …

Modern methods mainly regard lane detection as a problem of pixel-wise segmentation,
which is struggling to address the problem of challenging scenarios and speed. Inspired by …

The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …

In this paper, we propose a unified end-to-end trainable multi-task network that jointly
handles lane and road marking detection and recognition that is guided by a vanishing point …

Lane detection in driving scenes is an important module for autonomous vehicles and
advanced driver assistance systems. In recent years, many sophisticated lane detection …

Modern methods mainly regard lane detection as a problem of pixel-wise segmentation,
which is struggling to address the problems of efficiency and challenging scenarios like …

Automatic pavement crack segmentation plays a critical role in the field of defect inspection.
Although recent segmentation-based CNNs studies showed a promising pavement crack …