As a prerequisite for autonomous driving, scene understanding has attracted extensive
research. With the rise of the convolutional neural network (CNN)-based deep learning …

Autonomous vehicle is a kind of typical complex artificial intelligence system. In current
research of autonomous driving, the most widely adopted technique is to use a basic …

While most approaches to semantic reasoning have focused on improving performance, in
this paper we argue that computational times are very important in order to enable real time …

In this work, a deep learning approach has been developed to carry out road detection by
fusing LIDAR point clouds and camera images. An unstructured and sparse point cloud is …

Develo** neuromorphic intelligence on event-based datasets with Spiking Neural
Networks (SNNs) has recently attracted much research attention. However, the limited size …

End-to-end Network has become increasingly important in multi-tasking. One prominent
example of this is the growing significance of a driving perception system in autonomous …

Despite rapid developments in visual image-based road detection, robustly identifying road
areas in visual images remains challenging due to issues like illumination changes and …

Perception is an essential task for self-driving cars, but most perception tasks are usually
handled independently. We propose a unified neural network named DLT-Net to detect …

Maturity level-based classification system plays an essential role in the design of tomato
harvesting robot. Traditional knowledge-based systems are unable to meet the current …

Pixel-wise semantic segmentation is capable of unifying most of driving scene perception
tasks, and has enabled striking progress in the context of navigation assistance, where an …