首页|Findings from Aarhus University Yields New Data on Machine Learning (Quantificat ion of Aluminium Trihydrate Flame Retardant In Polyolefins Via In-line Hyperspec tral Imaging and Machine Learning for Safe Sorting)
Findings from Aarhus University Yields New Data on Machine Learning (Quantificat ion of Aluminium Trihydrate Flame Retardant In Polyolefins Via In-line Hyperspec tral Imaging and Machine Learning for Safe Sorting)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingout of Aarhus, Denmark, by NewsRx ed itors, research stated, “The extensive use of aluminium trihydrate(ATH) flame r etardant in plastics poses challenges and hazards in plastic waste recycling, th us it is crucialto accurately identify ATH. This study demonstrates the effecti veness of an industrial in-line shortwaveinfrared (SWIR) hyperspectral imaging system and principal component analysis (PCA) for detecting andquantifying ATH in low-density polyethylene (LDPE) and polypropylene (PP).”
AarhusDenmarkEuropeCyborgsEmergi ng TechnologiesFlame RetardantsMachine LearningAarhus University
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