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)

Robotics & Machine Learning Daily News2024，Issue(Nov.1) ：110-111.

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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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Abstract

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).

Key words

Beijing/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Chinese Academy of Sciences

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出版年

2024

Robotics & Machine Learning Daily News

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