首页|Findings from Duke University in Machine Learning Reported (Remotely sensed above-ground storage tank dataset for object detection and infrastructure assessment)
Findings from Duke University in Machine Learning Reported (Remotely sensed above-ground storage tank dataset for object detection and infrastructure assessment)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on artificial intelligence. According to news originatingfrom Duke University by NewsRx correspondents, research stated, “Remotely sensed imagery has increaseddramatically in quantity and public availability.”Funders for this research include Alfred P. Sloan Foundation; U.S. Environmental Protection Agency.The news journalists obtained a quote from the research from Duke University: “However, automated,large-scale analysis of such imagery is hindered by a lack of the annotations necessary to train and testmachine learning algorithms. In this study, we address this shortcoming with respect to above-groundstorage tanks (ASTs) that are used in a wide variety of industries. We annotated available high-resolution,remotely sensed imagery to develop an original, publicly available multi-class dataset of ASTs. This datasetincludes geospatial coordinates, border vertices, diameters, and orthorectified imagery for over 130,000ASTs from five labeled classes (external floating roof tanks, closed roof tanks, spherical pressure tanks,sedimentation tanks, and water towers) across the contiguous United States.”
Duke UniversityCyborgsEmerging TechnologiesMachine Learning
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