首页|Researchers at University of Saskatchewan Target Machine Learning (Machine Learn ing Approach for Satellite-based Subfield Canola Yield Prediction Using Floral P henology Metrics and Soil Parameters)
Researchers at University of Saskatchewan Target Machine Learning (Machine Learn ing Approach for Satellite-based Subfield Canola Yield Prediction Using Floral P henology Metrics and Soil Parameters)
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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 reporting outof Saskatoon, Canada, by NewsRx editors, research stated, “Early monitoring of within-field yield variabilityan d forecasting yield potential is critical for farmers and other key stakeholders such as policymakers.Remote sensing techniques are progressively being used in yield prediction studies due to easy access andaffordability.”
SaskatoonCanadaNorth and Central Ame ricaCyborgsEmerging TechnologiesMachine LearningRemote SensingUniversi ty of Saskatchewan
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