Object detection in optical remote sensing images, being a fundamental but challenging
problem in the field of aerial and satellite image analysis, plays an important role for a wide …

Semantic segmentation is an essential part of deep learning. In recent years, with the
development of remote sensing big data, semantic segmentation has been increasingly …

The automated man-made object detection and building extraction from single satellite
images is, still, one of the most challenging tasks for various urban planning and monitoring …

Building extraction from remote sensing images is of great importance in urban planning.
Yet it is a longstanding problem for many complicate factors such as various scales and …

Object detection from remote sensing images (RSIs) is a basic topic in the area of aviation
and satellite image processing, which has great effects on geological disaster detection …

Automatic building extraction from High-Resolution Satellite (HRS) image has been an
important field of research in the area of remote sensing. Different techniques related to …

Given the importance and interest of buildings in the urban environment, numerous studies
have focused on automatically extracting building outlines by exploiting different datasets …

In this paper, two main approaches for automatic building detection and localization using
high spatial resolution imagery and LiDAR data are compared and evaluated: thresholding …

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

In recent years, the Dataset for Object deTection in Aerial images (DOTA) dataset has
played a pivotal role in advancing object detection in aerial images (ODAI). Despite its …