Given the large volume of remote sensing images collected daily, automatic object detection
and segmentation have been a consistent need in Earth observation (EO). However, objects …

Object classification is a crucial yet challenging vision ability to perfect The fundamental
objective is to educate computers to understand visuals the same way humans do. Due to …

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 …

Benchmark datasets are critical for develo**, evaluating, and comparing remote sensing
image retrieval (RSIR) approaches. However, current benchmark datasets are deficient in …

The rapid development of remote sensing technology has facilitated us the acquisition of
remote sensing images with higher and higher spatial resolution, but how to automatically …

An automatic system to extract terrestrial objects from aerial imagery has many applications
in a wide range of areas. However, in general, this task has been performed by human …

This paper investigates local invariant features for geographic (overhead) image retrieval.
Local features are particularly well suited for the newer generations of aerial and satellite …

Automatic detection of geospatial targets in cluttered scenes is a profound challenge in the
field of aerial and satellite image analysis. In this paper, we propose a novel practical …

Satellite images can provide valuable information about the presented urban landscape
scenes to remote sensing and telecommunication applications. Obtaining information from …

Object detection in very high-resolution (VHR) aerial images is an essential step for a wide
range of applications such as military applications, urban planning, and environmental …