首页|New Machine Learning Findings from China Agricultural University Described (Mach ine Learning Techniques and Interpretability for Maize Yield Estimation Using Ti me-series Images of Modis and Multi-source Data)
New Machine Learning Findings from China Agricultural University Described (Mach ine Learning Techniques and Interpretability for Maize Yield Estimation Using Ti me-series Images of Modis and Multi-source Data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reporting fromBeijing, People’s Republic of China , by NewsRx journalists, research stated, “Timely and accurate estimationof mai ze yield is crucial for ensuring food security. This study integrated multisourc e data (satellite,meteorological, and soil data) on Google Earth Engine (GEE) a nd used machine learning techniques toestimate summer maize yield across 469 co unties in the Huang -Huai -Hai Plain of China from 2010 to2020.”
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningRemote SensingChina Agric ultural University
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