Satellite Terrain Data and Machine Learning Reveal Where Soil Quality Fails
Researchers in northern Iran combined satellite-derived terrain attributes with a support vector machine and factor analysis to map soil quality, ...
Researchers in northern Iran combined satellite-derived terrain attributes with a support vector machine and factor analysis to map soil quality, ...
Chinese researchers used extractive electrospray ionization mass spectrometry and machine learning to detect lung cancer from exhaled breath with over ...
A new EEG study finds that altered transitions between the brain's brief electrical microstates, combined with source-space connectivity features, can ...
An integrated 18F-NOTA-FAPI-04 PET/MRI approach combining fibroblast-targeted molecular imaging with quantitative MRI features outperforms either modality alone in distinguishing active ...
A three-year Georgia field study found that machine learning models fed PlanetScope satellite vegetation indices could not reliably predict peanut ...
Researchers paired a validated PLAXIS 3D finite element model with kernel-based Support Vector Machines to predict soil bearing capacity with ...
Brazilian researchers have combined vibration analysis with explainable artificial intelligence to diagnose unbalance, misalignment, and cracks in rotors supported by ...
A new study in Water Resources Management shows that Random Forest and other machine learning models can forecast daily suspended ...
Researchers at the CDC and Emory University have built a machine learning-powered database that automatically curates the rapidly growing literature ...
Researchers in West Bengal fused the Analytic Hierarchy Process with Random Forest, Logistic Regression, and Support Vector Machine models to ...
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© 2025 Scienmag - Science Magazine