This paper surveys the state-of-the-art automatic object extraction techniques from aerial
imagery. It focuses on building extraction approaches, which present the majority of the work …

Road information from high-resolution remote-sensing images is widely used in various
fields, and deep-learning-based methods have effectively shown high road-extraction …

This paper deals with semantic segmentation of high-resolution (aerial) images where a
semantic class label is assigned to each pixel via supervised classification as a basis for …

摘要自动道路提取是遥感图像识别的重要研究领域. 实现自动化, 智能化, 可靠准确的图像道路
提取对地理信息技术发展具有重要的应用价值和意义. 道路的物理属性和功能形成了道路的辐射 …

Extracting roads from high-resolution remote sensing images (HRSIs) is vital in a wide
variety of applications, such as autonomous driving, path planning, and road navigation …

The extraction of curvilinear structures is an important low-level operation in computer vision
that has many applications. Most existing operators use a simple model for the line that is to …

针对道路目标特点, 设计实现了用于遥感影像道路提取的Encoder-Decoder 深度语义分割网络.
首先, 针对道路目标局部特征丰富, 语义特征较为简单的特点, 设计了较浅深度 …

Road segmentation from remote sensing images is an important task in many applications.
However, due to the high density of roads and the complex background, the roads are often …

Mission-critical applications that rely on deep learning (DL) for automation suffer because
DL models struggle to provide reliable indicators of failure. Reliable failure prediction can …

Airborne lidar has become a commercially viable remote sensing platform, and can provide
accurate elevation data about both topographic surfaces and non-terrain objects. Its …