In recent years, deep learning has significantly reshaped numerous fields and applications,
fundamentally altering how we tackle a variety of challenges. Areas such as natural …

Abstract Synthetic Aperture Radar (SAR) observations, valued for their consistent acquisition
schedule and not being affected by cloud cover and variations between day and night, have …

Abstract Machine learning is an evolving branch of computational algorithms that are
designed to emulate human intelligence by learning from the surrounding environment …

Instance segmentation is the state-of-the-art in object detection, and there are numerous
applications in remote sensing data where these algorithms can produce significant results …

Effective water management requires a large-scale understanding of agricultural irrigation
systems and how they shift in response to various stressors. Here, we leveraged advances …

Brazil is a tropical country with continental dimensions and abundant solar resources that
are still underutilized. However, solar energy is one of the most promising renewable …

Historic topographic maps, which are georeferenced and made publicly available by the
United States Geological Survey (USGS) and the National Map's Historical Topographic …

The automatic and accurate detection of mangroves from remote sensing data is essential to
assist in conservation strategies and decision-making that minimize possible environmental …

Oil spills are a worldwide concern since they cause environmental problems and financial
losses. Automatic detection plays a crucial role in rapid decision-making to reduce damage …

Panoptic segmentation combines instance and semantic predictions, allowing the detection
of countable objects and different backgrounds simultaneously. Effectively approaching …