Deep Learning Framework Improves Hub-Height Wind Speed Estimates for Power Projections
Researchers developed a ResUNet deep learning framework that simultaneously downscales near-surface winds and estimates hub-height wind speeds for wind power ...
Researchers developed a ResUNet deep learning framework that simultaneously downscales near-surface winds and estimates hub-height wind speeds for wind power ...
A task-based phantom study demonstrates that deep-learning CT reconstruction with high-frequency kernels substantially reduces image noise while preserving spatial resolution, ...
A phantom and simulation study shows that Yttrium-90 digital PET imaging achieves absorbed dose errors under ten percent in large ...
High-resolution satellite imagery significantly outperforms coarse maps for planning and assessing prescribed fires in sagebrush rangelands, according to a new ...
A clinical review outlines photon-counting CT advantages and its potential to enhance tumor detection and treatment response assessment in abdominal ...
Researchers have developed a localized machine learning framework that sharpens reconstructed PET scans and reduces noise by approximating Bayesian deconvolution ...
Researchers have developed a multifunctional anthropomorphic phantom designed to simultaneously evaluate key performance metrics for nuclear medicine imaging systems.
An attenuation correction method for single-ended Raman distributed temperature sensors achieved ±0.8 °C accuracy over 20–70 °C on a 450 ...
A cross-sensor comparison of GOCI-II, Sentinel-2 and Sentinel-3 observations of two 2021 East China Sea harmful algal blooms shows that ...
Controlled-release tests established a median 50% detection limit of 99.0 ± 5.3 kg h−1 for GHGSat satellites under specified test ...
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© 2026 Scienmag - Science Magazine