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 …

We give a methodology-oriented perspective on directional image analysis and rotation-
invariant processing. We review the state of the art in the field and make connections with …

Extracting roads from satellite imagery is a promising approach to update the dynamic
changes of road networks efficiently and timely. However, it is challenging due to the …

Creating road maps is essential to the success of many applications such as autonomous
driving and city planning. Most approaches in industry focus on leveraging expensive …

Map** road networks is currently both expensive and labor-intensive. High-resolution
aerial imagery provides a promising avenue to automatically infer a road network. Prior work …

Recent years have seen an unprecedented spread of Unmanned Aerial Vehicles (UAVs, or
“drones”), which are highly useful for both civilian and military applications. Flight safety is a …

The knowledge of impervious surfaces, especially the magnitude, location, geometry, spatial
pattern of impervious surfaces and the perviousness–imperviousness ratio, is significant to a …

Extracting road maps from high-resolution optical remote sensing images has received
much attention recently, especially with the rapid development of deep learning methods …

2013-11-13 Assigned to APPLE INC. reassignment APPLE INC. ASSIGNMENT OF
ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: Bennett, Jonathan …

Reliably extracting information from aerial imagery is a difficult problem with many practical
applications. One specific case of this problem is the task of automatically detecting roads …