6 datasets found
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Federal
Training and validation data from the AI for Critical Mineral Assessment Competition (ver. 2.0, July 2025)
Department of the Interior —
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort.... -
Federal
Training and Validation Datasets for Neural Network to Fill in Missing Data in EBSD Maps
National Institute of Standards and Technology —
This dataset consists of the synthetic electron backscatter diffraction (EBSD) maps generated for the paper, titled "Hybrid Algorithm for Filling in Missing Data in... -
Federal
Map georeferencing challenge training and validation data
Department of the Interior —
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort.... -
Federal
Map feature extraction challenge training and validation data
Department of the Interior —
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort.... -
Federal
GeoNatShapes: a natural feature reference dataset for mapping and AI training
Department of the Interior —
These data were compiled for the use of training natural feature machine learning (GeoAI) detection and delineation. The natural feature classes include the... -
Federal
GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Department of Energy —
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal...
6 datasets found