首页|Data on Machine Learning Discussed by Researchers at Chinese Academy of Sciences (A Practical Machine Learning Approach To Retrieve Land Surface Emissivity From Space Using Visible and Near-infrared To Short-wave Infrared Data)
Data on Machine Learning Discussed by Researchers at Chinese Academy of Sciences (A Practical Machine Learning Approach To Retrieve Land Surface Emissivity From Space Using Visible and Near-infrared To Short-wave Infrared Data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news originating from Beijing, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Land surface emissiv ity (LSE) is a crucial variable in thermal infrared (TIR) remote sensing, provid ing unique information about the land surface across different channels. It is e ssential for applications such as surface energy budget estimation, resource exp loration, and land cover change monitoring.” Funders for this research include National Key R & D Program of Ch ina, National Natural Science Foundation of China (NSFC).
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningChinese Academy of Sciences
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