Search results for machine learning

Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

Australian Ocean Data Network · Updated 23 Jun 2026

… In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

Australian Ocean Data Network · Updated 27 Jun 2026

… In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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Data from paper entitled "Explainable machine learning to identify activity-related, insulin and dietary thresholds for prevention of exercise-associated hypoglycaemia and hyperglycaemia in free-living children with type 1 diabetes"

IQBAL, Asif · Updated 18 Feb 2026

… Ensemble machine-learning models predicted hypoglycaemia (<70 mg·dL⁻¹) and hyperglycaemia (>180 mg·dL⁻¹) during exercise …

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Executive Branch Artificial Intelligence System Inventory

data.ct.gov · Updated 8 Dec 2025

… learning, communication, decision-making or action, or (B) a set of techniques, including, but not limited to, machine …

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Appendices for Geothermal Exploration Artificial Intelligence Report

Colorado School of Mines · Updated 13 Jan 2022

The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This …

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Spectres infrarouge OPTIR de drèches de brasserie et de dix molécules organiques associées

Lagneaux, Paul · Updated 26 May 2026

Lien vers la fiche source OPTIR (Optical Photothermal InfraRed) infrared spectra of 10 organic molecules: starch, arabinose, glucose …

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Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)

National Renewable Energy Laboratory (NREL) · Updated 14 Jul 2026

… The downscaling process was performed using a generative machine learning approach called sup3r: Super-Resolution for Renewable Energy …

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CCDR: Volume 46-6 -June 2020: Artificial intelligence in public health

Public Health Agency of Canada | Agence de la santé publique du Canada · Updated 5 Jun 2020

The Canada Communicable Disease Report is a bilingual, open-access, peer-reviewed journal on the prevention and control …

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Tri-axial acceleration data from California condors (Gymnogyps californianus), California, USA

U.S. Geological Survey · Updated 6 Sept 2024

We outfitted nine condors in a flight pen with patagial tags, each with a unique ID, and a …

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Ensemble precipitation forecasts made with Quantile Regression Forests and deterministic Harmonie-Arome inputs

NationaalGeoregister.nl · Updated 19 Aug 2026

A gridded 51-member ensemble of precipitation forecasts that are created using a tree-based machine learning method …

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Data to estimate urban seismic damages and debris from building-level simulations

Rouba Iskandar · Updated 5 Nov 2024

Lien vers la fiche source This dataset contains informations about buildings in Beirut in shapefile format used for …

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Ecomapper Dataset

open.bydata · Updated 11 Nov 2026

The EcoMapper dataset comprises over 2.9 million satellite images accompanied by climate metadata. It includes both RGB …

Data from: Topographic position index predicts within-field yield variation in a dryland cereal production system

Agricultural Research Service · Updated 21 Nov 2025

We investigated drivers of sub-field spatial variability in yield for 3 crops (hard red winter wheat, Triticum …

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Automated Fish Detection and Wildlife Tracking for Marine Energy Applications: Final Report and Review

Booz Allen Hamilton Inc. · Updated 17 Aug 2026

… The project analyzes how modern computer-vision and machine-learning techniques can support reductions in manual labor, improve …

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Data from: Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth

Agricultural Research Service · Updated 2 May 2025

Two field research projects focused on cotton were conducted at the El Reno, OK and Temple, TX USDA …

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AOML_ET: Partial pressure of CO2 (pCO2) and sea-air CO2 fluxes for the global ocean, along with the predictor variables from 1998-01-01 to 2023-12-30, using an Extra Trees (extremely randomized trees) machine learning (NCEI Accession 0298989)

NOAA National Centers for Environmental Information · Updated 21 Nov 2024

… the extremely randomized trees or extra trees, ET machine learning approach. The products are labeled as AOML_ET …

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METALLICADOUR: Détection et diagnostic des défauts dans les robots multi-axes

Soualhi, Moncef · Updated 11 Sept 2025

… This latter motor drives a cutting tool for machining aluminum parts. It studies different states of health of …

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LASPI: Détection et diagnostic des défauts de boîte de vitesses

Soualhi, Moncef · Updated 8 Sept 2025

Lien vers la fiche source Dataset of current, voltage, and vibration measurements of an electromechanical driving system. The …

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Annotated images taken from the video feed from traffic cameras (archives)

Government and Municipalities of Québec | Gouvernement et municipalités du Québec · Updated 27 May 2026

Images extracted from the recordings of [road observation cameras] (http://ville.montreal.qc.ca/circulation/) accompanied by annotations …

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Machine learning model that estimates total monthly and annual per capita public-supply water use (version 2.0)

U.S. Geological Survey · Updated 27 Aug 2024

This child item describes a machine learning model that was developed to estimate public-supply water use by …

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