首页|Researchers at Northwest A&F University Report New Data on Machine Learning [Integrating Multi-source Remote Sensing and Machine Learning for Root-zone Soil Moisture and Yield Prediction of Winter Oilseed Rap e ( Brassica Napus L.): …]
Researchers at Northwest A&F University Report New Data on Machine Learning [Integrating Multi-source Remote Sensing and Machine Learning for Root-zone Soil Moisture and Yield Prediction of Winter Oilseed Rap e ( Brassica Napus L.): …]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. Accordingto news reporting originating from Yang ling, People’s Republic of China, by NewsRx correspondents,research stated, “Ac curately assessing root-zone soil moisture is crucial for precision irrigation, as itdirectly influences crop yield. The Temperature-Vegetation Index (Ts-VI) F eature Space, which combinesland surface temperature (Ts) and vegetation index (VI), is widely used to evaluate root-zone soil moisturein vegetated areas.”
YanglingPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningRemote SensingNorthwest A&F University
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