首页|Studies from University of Debrecen Further Understanding of Machine Learning (P risma Vs. Landsat 9 In Lithological Mapping - a K-fold Cross-validation Implemen tation With Random Forest)
Studies from University of Debrecen Further Understanding of Machine Learning (P risma Vs. Landsat 9 In Lithological Mapping - a K-fold Cross-validation Implemen tation With Random Forest)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reporting fromDebrecen, Hungary, by NewsRx journa lists, research stated, “The selection of an optimal dataset is crucialfor succ essful remote sensing analysis. The PRISMA hyperspectral sensor (with 240 spectr al bands) and Landsat OLI-2 (boasting high dynamic resolution) offer robust data for various remote sensing applications,anticipating their increased demand in the coming years.”
DebrecenHungaryEuropeCyborgsEmer ging TechnologiesMachine LearningRemote SensingUniversity of Debrecen
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