Building detection from very high resolution (VHR) optical remote sensing images, which is
an essential but challenging task in remote sensing, has attracted increased attention in …

Deep learning methods based upon convolutional neural networks (CNNs) have
demonstrated impressive performance in the task of building outline delineation from very …

The identification and annotation of buildings has long been a tedious and expensive part of
high-precision vector map production. The deep learning techniques such as fully …

Buildings are the most striking artificial features, and extracting buildings becomes critical for
many service-providing agencies. Although improvements have been achieved, building …

Research has developed numerous algorithms to simplify building data. Each algorithm has
strengths and weaknesses in addressing shape characteristics, but no single algorithm can …

Automatic building rooftop extraction is of great importance to many applications including
building reconstruction, solar energy supply, and disaster management. This study proposes …

As the basic feature of building, building edges play an important role in many fields such as
urbanization monitoring, city planning, surveying and mapping. Building edges detection …

Automatic building extraction from satellite images, an open research topic in remote
sensing, continues to represent a challenge and has received substantial attention for …

Polyline and building simplification remain challenging in cartography. Most proposed
algorithms are geometric-based and rely on specific rules. In this study, we propose a deep …

建筑物化简是地图制图领域关注的热点问题之一. 集成不同算法构建形状特征自适应的化简模型
是应对建筑物多样化形态的有效策略, 但当前相关研究主要从局部结构模式或化简结果评价展开 …