Machine Learning and Hyperspectral Imaging Reveal Lead in Rice Leaves from Space
Researchers have identified the most reliable machine learning pipeline for estimating toxic lead levels in rice leaves from hyperspectral satellite ...
Researchers have identified the most reliable machine learning pipeline for estimating toxic lead levels in rice leaves from hyperspectral satellite ...
Researchers paired graphene and cellulose nanoparticles with a genetic-algorithm-optimized neural network to predict hybrid nanofluid performance, achieving a 52.77 percent ...
Researchers in Beijing built logistic regression and XGBoost models that predict bone scintigraphy diagnostic categories before scanning, finding that probability ...
A bibliometric analysis of nearly 10,000 publications shows that AI-driven biomimetics is thriving in robotics and computing while energy applications ...
Penn State researchers adapted diffusion-based generative AI techniques from image generation to build an hourly flood forecasting model trained on ...
A new study in Earth's Future projects that climate change will boost European sorghum yields enough to replace roughly 90 ...
German researchers show that hyperspectral imaging combined with machine learning can distinguish parental and hybrid faba bean seeds, opening a ...
A new review argues that merging finite-element cardiac modeling, 3D-printed patient-specific phantoms, and artificial intelligence into digital–physical twins could reshape ...
A multi-year Texas study combining drone imaging, machine learning, and explainable AI shows that wheat yield is best predicted from ...
Researchers used weekly lead measurements in baby teeth and machine learning to reconstruct cord blood lead concentrations at birth, offering ...
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© 2025 Scienmag - Science Magazine