首页|Studies from Georg-August-University Further Understanding of Machine Learning (From Outcrop To Spectrum-an Automated Approach To Modal Mineralogy of Silt-sized Sediment Applied To Central European Loess)
Studies from Georg-August-University Further Understanding of Machine Learning (From Outcrop To Spectrum-an Automated Approach To Modal Mineralogy of Silt-sized Sediment Applied To Central European Loess)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learning have been published. According to newsreporting originating from Gottingen, Germany, by NewsRx correspondents, research stated, “Provenanceinformation from recent and ancient sedimentary archives is obscured by several factors and for disentanglingthese intermingled signals, analysis by multiple methods is paramount. In sedimentary provenance analysis(SPA), single-grain methods determining mineralogy, chemical composition, or radiometric ages are of keyimportance but are mostly applied to sand-sized sediments or sedimentary rocks.”
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