首页|Study Findings on Machine Learning Are Outlined in Reports from University of Ca diz (Combining Low-loss Eels Experiments With Machine Learning-based Algorithms To Automate the Phases Separation Imaging In Industrial Duplex Stainless Steels)
Study Findings on Machine Learning Are Outlined in Reports from University of Ca diz (Combining Low-loss Eels Experiments With Machine Learning-based Algorithms To Automate the Phases Separation Imaging In Industrial Duplex Stainless Steels)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Cadiz, Spain, by NewsR x correspondents, research stated, "At present, transmission electron microscopy is regarded as the main option when dealing with phase characterization for mat erials at a nanometric scale. The development and improvement of complementary t echniques such as energydispersive X-ray spectroscopy (EDS), electron energy lo ss spectroscopy (EELS), imaging detectors and associated computational methods p rovide a huge variety of choices to determine the composition and crystal struct ure at any region of a specimen." Financial supporters for this research include Spanish Government, Ministerio de Ciencia e Innovacion MCIN/AEI/FEDER UE, European Union "NextGenerationEU"/PRTR.
CadizSpainEuropeAlgorithmsCyborg sEmerging TechnologiesMachine LearningStainless SteelUniversity of Cadiz
NETL
NSTL
