Semantic segmentation of drone images is critical to many aerial vision tasks as it provides
essential semantic details that can compensate for the lack of depth information from …

Semantic segmentation has been one of the leading research interests in computer vision
recently. It serves as a perception foundation for many fields, such as robotics and …

The availability of high-resolution imagery resources for semantic segmentation research
has expanded significantly due to the rapid development of remote-sensing technology …

In this paper, we propose an improved training protocol of U-Net architecture for the
semantic segmentation of aerial images. We test our approach on the challenging FLAIR# 2 …

Semantic segmentation of high-resolution aerial images is a challenging task on account of
interclass homogeneity and intraclass heterogeneity of land cover. Recent works have …

Ensuring the safety of all traffic participants is a prerequisite for bringing intelligent vehicles
closer to practical applications. The assistance system should not only achieve high …

This research addresses the crucial task of improving accuracy in the semantic
segmentation of aerial imagery, essential for applications such as urban planning and …

Recent advances on aerial image semantic segmentation mainly employ the domain
adaption to transfer knowledge from the source domain to the target domain. Despite the …

Fast semantic image segmentation is crucial for autonomous systems, as it allows an
autonomous system (eg, self-driving car, drone, etc.) to interpret its environment on-the-fly …

Capturing accurate multiscale semantic information from the images is of great importance
for high-quality semantic segmentation. Over the past years, a large number of methods …