Population growth, climate change, and the worldwide COVID-19 pandemic are imposing
increasing pressure on global agricultural production. The challenge of increasing crop yield …

The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …

Ship classification in synthetic aperture radar (SAR) images is a fundamental and significant
step in ocean surveillance. Recently, with the rise of deep learning (DL), modern abstract …

Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …

Synthetic aperture radar (SAR) is playing an important role in maritime domain awareness.
As a fundamental ocean mission, SAR ship detection can offer high-quality services for …

Abstract Ship detection from Synthetic Aperture Radar (SAR) imagery is attracting increasing
attention due to its great value in ocean. However, existing most studies are frequently …

There has been a recent emphasis on integrating physical models and deep neural
networks (DNNs) for SAR target recognition, to improve performance and achieve a higher …

The recognition or understanding of the scenes observed with a synthetic aperture radar
(SAR) system requires a broader range of cues beyond the spatial context. These …

Ship detection and classification pose significant challenges in remote sensing. The potent
feature extraction capabilities of deep learning algorithms render them pivotal for these …

Automatic and high-precision extraction of buildings from remote sensing images has a wide
range of application and importance. Optical and synthetic aperture radar (SAR) images are …