首页|Researchers from UNSW Describe Findings in Machine Learning (Extracting the Para meters of Two-energy-level Defects In Silicon Wafers Using Machine Learning Models)
Researchers from UNSW Describe Findings in Machine Learning (Extracting the Para meters of Two-energy-level Defects In Silicon Wafers Using Machine Learning Models)
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 Daily News – Research findings on Machine Learning are discussed in a new report. According to news originating from Sydney, Austra lia, by NewsRx correspondents, research stated, “This study introduces a pioneer ing machine learning (ML)-based methodology to characterise two-level defects in the bulk of silicon wafers. Bulk defects have a critical impact on the efficiency of silicon solar cells.”
SydneyAustraliaAustralia and New Zea landCyborgsEmerging TechnologiesMachine LearningUNSW
NETL
NSTL
