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Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training and validation data from the map feature extraction challenge are provided here, as well as competition details and a baseline solution. The data were derived from published sources and are provided...
Categories: Data;
Tags: AI,
Artificial Intelligence,
GIS,
ML,
North America, All tags...
competition,
critical mineral resources,
digitization,
economy,
geological maps,
geoscientificInformation,
geospatial datasets,
machine learning,
modeling,
resource assessment,
tool development,
topographic maps,
training data, Fewer tags
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Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training and validation data from the map georeferencing challenge are provided here, as well as competition details and a baseline solution. The data were derived from published sources and are provided...
Categories: Data;
Tags: AI,
Artificial Intelligence,
GIS,
ML,
North America, All tags...
competition,
critical mineral resources,
digitization,
economy,
geological maps,
geoscientificInformation,
geospatial datasets,
machine learning,
modeling,
resource assessment,
tool development,
topographic maps,
training data, Fewer tags
|
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training and validation data from the competition are provided here, as well as competition details and baseline solutions. The data are derived from published sources and are provided to the public to...
Categories: Data;
Tags: "Geography"],
"Mineral Resources",
AI,
Artificial Intelligence,
GIS, All tags...
ML,
North America,
USGS Science Data Catalog (SDC),
["Economic Geology",
competition,
critical mineral resources,
digitization,
economy,
geological maps,
geoscientificInformation,
geospatial datasets,
machine learning,
modeling,
resource assessment,
tool development,
topographic maps,
training data, Fewer tags
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