Hestia Fossil Fuel Carbon Dioxide Emissions Inventory for Urban Regions (Hestia FFCO2) provides data products for Los Angeles Basin, Northeast corridor, Indianapolis, and other U.S. Cities. Hestia FFCO2 datasets quantify greenhouse gases (GHG), such as carbon dioxide, emitted by urban regions, since cities are major contributors of anthropogenic GHG emissions. The Hestia FFCO2 datasets provide high spatial and temporal resolution CO2 concentrations at sub-county resolutions and annual/hourly time scales, specific to the region.

Hestia Project quantifies, simulates and visualizes greenhouse gases such as carbon dioxide emitted in urban regions. Indianapolis data is provided at the county level (200 m grid resolution), and at hourly and yearly time frames. It builds upon work conducted at the national scale by the Vulcan Project. These high spatial and temporal resolution datasets are available from 2010 to 2015.

Hestia Project quantifies, simulates and visualizes greenhouse gases such as carbon dioxide emitted in urban regions. Baltimore, Maryland activity is provided at the county level (200 m grid resolution), and at hourly and yearly time frames. It builds upon work conducted at the national scale by the Vulcan Project. These high spatial and temporal resolution datasets are available from 2010.

Hestia Project quantifies, simulates and visualizes greenhouse gases such as carbon dioxide emitted in urban regions. Salt Lake City, Utah activity is provided at the county level (0.002 degree grid resolution), and at hourly and yearly time frames. It builds upon work conducted at the national scale by the Vulcan Project. These high spatial and temporal resolution datasets are available for 2002, 2010, 2011, and 2012.

Round 3 Training DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 2 Test DatasetThe data being generated and disseminated is the test data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 2 Holdout DatasetThe data being generated and disseminated is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 3 Test DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 3 Holdout DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 4 Train DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.