首页|Reports from Ludong University Advance Knowledge in Machine Learning (Power of S ar Imagery and Machine Learning In Monitoring ulva Prolifera: a Case Study of Se ntinel-1 and Random Forest)
Reports from Ludong University Advance Knowledge in Machine Learning (Power of S ar Imagery and Machine Learning In Monitoring ulva Prolifera: a Case Study of Se ntinel-1 and Random Forest)
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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 tonews originating from Yantai, People’s Rep ublic of China, by NewsRx correspondents, research stated,“Automatically detect ing Ulva prolifera (U. prolifera) in rainy and cloudy weather using remote sensi ngimagery has been a long-standing problem. Here, we address this challenge by combining high-resolutionSynthetic Aperture Radar (SAR) imagery with the machin e learning, and detect the U. prolifera of theSouth Yellow Sea of China (SYS) i n 2021.”
YantaiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningLudong University
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