首页|Reports on Machine Learning from Ulm University Provide New Insights (Multidimensional Characterization of Particle Morphology and Mineralogical Composition Using Ct Data and R-vine Copulas)
Reports on Machine Learning from Ulm University Provide New Insights (Multidimensional Characterization of Particle Morphology and Mineralogical Composition Using Ct Data and R-vine Copulas)
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 DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingout of Ulm, Germany, by NewsRx editors, research stated, “Computed tomography (CT) can capture volumeslarge enough to measure a statistically meaningful number of micron-sized particles with a sufficientlygood resolution to allow for the analysis of individual particles. However, the development of methods toefficiently investigate such image data and interpretably model the observed particle features is still anactive field of research.”
UlmGermanyEuropeCyborgsEmerging TechnologiesMachine LearningUlm University
NETL
NSTL
