Perception techniques for autonomous driving should be adaptive to various environments.
In essential perception modules for traffic line detection, many conditions should be …

Semantic segmentation of urban scenes is an essential component in various applications
of autonomous driving. It makes great progress with the rise of deep learning technologies …

The semantic segmentation of road scenes is an important task in autonomous driving.
Deep learning has enabled the development of a variety of semantic segmentation networks …

Joint detection of drivable areas and road anomalies is very important for mobile robots.
Recently, many semantic segmentation approaches based on convolutional neural …

Freespace detection is a fundamental component of autonomous driving perception.
Recently, deep convolutional neural networks (DCNNs) have achieved impressive …

Supervised learning with deep convolutional neural networks (DCNNs) has seen huge
adoption in stereo matching. However, the acquisition of large-scale datasets with well …

In several existing red–green–blue and depth (RGB-D) semantic segmentation algorithms,
schemes are used to supplement contextual information through multilayer feature …

The joint detection of drivable areas and road anomalies is a crucial task for ground mobile
robots. In recent years, many impressive semantic segmentation networks, which can be …

Small-sized unmanned surface vehicles (USV) are coastal water devices with a broad range
of applications such as environmental control and surveillance. A crucial capability for …

In recent years, automatic mobile robots (AMRs) have been widely concerned in various
fields, such as material handling, unmanned aerial vehicle (UAV) cruise, automatic factories …