Automated extraction of roads from remotely sensed data come forth various usages ranging
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …

Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …

Unmanned aerial vehicles (UAVs) have recently rapidly grown to facilitate a wide range of
innovative applications that can fundamentally change the way cyber-physical systems …

Urban building segmentation is a prevalent research domain for very high resolution (VHR)
remote sensing; however, various appearances and complicated background of VHR …

Automatic road extraction from high-resolution remote sensing imagery has various
applications like urban planning and automatic navigation. Existing methods for automatic …

Combining an object-detection algorithm with an unmanned aerial vehicle (UAV) can
accelerate the detection of road cracks. To address the difficulties of intricate crack …

In this article, we propose a solution to the problem of path following for a quadcopter aircraft
with unknown vehicle parameters (mass and moment of inertia) and external disturbances …

Few-shot semantic segmentation, aiming to segment query images with a few annotated
support samples, has drawn increasing attention. Most existing few-shot methods leverage …

The widespread use of mobile devices and sensors has motivated data-driven applications
that can leverage the power of big data to benefit many aspects of our daily life, such as …

Fully supervised road segmentation neural networks from remote sensing images rely on a
large number of densely labeled road samples, limiting their potential in large-scale …