首页|Stellenbosch University Reports Findings in Machine Learning (An open-source machine-learning approach for obtaining high-quality quantitative wood anatomy data from E. grandis and P. radiata xylem)
Stellenbosch University Reports Findings in Machine Learning (An open-source machine-learning approach for obtaining high-quality quantitative wood anatomy data from E. grandis and P. radiata xylem)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Machine Learning is the subject of a report. According to news reporting outof Stellenbosch, South Africa, by NewsRx editors, research stated, “Quantitative wood anatomy is asubfield in dendrochronology that requires effective open-source image analysis tools. In this research, thebioimage analysis software QuPath (v0.4.4) is introduced as a candidate for accurately quantifying thecellular properties of the xylem in an automated manner.”
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