Mixture-of-Experts AI Model Brings Fine-Grained Vision to High-Resolution Satellite Imagery
A new mixture-of-experts vision-language model called RSFG-MoE is designed to deliver fine-grained, high-resolution interpretation of remote sensing imagery.
A new mixture-of-experts vision-language model called RSFG-MoE is designed to deliver fine-grained, high-resolution interpretation of remote sensing imagery.
A new satellite-based study fusing six vegetation indicators finds that roughly 30 percent of the Horn of Africa's grasslands are ...
A new random forest model with spatial cross-validation reveals that slope and topographic relief control landslide hazards along the Lhasa–Dingri ...
A comprehensive review shows that artificial intelligence, from hyperspectral sensing and climate-driven forecasting to autonomous drones and ground robots, is ...
A new 1-kilometer grid-based screening framework links two decades of fine particulate pollution with satellite-derived water quality signals across the ...
A new dual-branch deep learning framework combining GAN-based super-resolution and transformer spectral modeling achieves over 99 percent accuracy classifying hyperspectral ...
University of Utah-led research shows satellite measurements of solar-induced fluorescence detected declining photosynthetic activity in Western U.S. forests two years ...
A 24-year satellite and machine learning study shows Bharatpur's heat island is expanding across the city rather than intensifying at ...
A feature-optimized machine learning framework using MODIS satellite data achieves highly accurate estimation of crop vegetation water stress in Egypt's ...
A comparative review finds that decades of built-up expansion have driven rising land surface temperatures in India's World Heritage Cities ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine