首页|Reports from Chinese Academy of Sciences Describe Recent Advances in Machine Lea rning (Spatial-temporal Distribution of Labeled Set Bias Remote Sensing Estimati on: an Implication for Supervised Machine Learning In Water Quality Monitoring)
Reports from Chinese Academy of Sciences Describe Recent Advances in Machine Lea rning (Spatial-temporal Distribution of Labeled Set Bias Remote Sensing Estimati on: an Implication for Supervised Machine Learning In Water Quality Monitoring)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting out of Wuhan, People’s Repu blic of China, by NewsRx editors, research stated, “Supervisedmachine learning (SML) has become a crucial tool for estimating water quality parameters (WQPs) f romsatellite images. Its effectiveness relies heavily on synchronised in-situ d atasets covering diverse waterbodies.”
WuhanPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningRemote SensingChinese Acade my of Sciences
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