首页|Studies from Stanford University Provide New Data on Machine Learning (Subfield- level Crop Yield Mapping Without Ground Truth Data: a Scale Transfer Framework)
Studies from Stanford University Provide New Data on Machine Learning (Subfield- level Crop Yield Mapping Without Ground Truth Data: a Scale Transfer Framework)
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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 originatingfrom Stanford, California, by NewsRx c orrespondents, research stated, “Ongoing advances in satelliteremote sensing da ta and machine learning methods have enabled crop yield estimation at various sp atialand temporal resolutions. While yield mapping at broader scales (e.g., sta te or county level) has becomecommon, mapping at finer scales (e.g., field or s ubfield) has been limited by the lack of ground truth datafor model training an d evaluation.”
StanfordCaliforniaUnited StatesNor th and Central AmericaCyborgsEmerging TechnologiesMachine LearningStanfo rd University
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