首页|Findings from University of Leuven (KU Leuven) Provides New Data about Machine L earning (A Machine Learning Approach for Estimating Snow Depth Across the Europe an Alps From Sentinel-1 Imagery)
Findings from University of Leuven (KU Leuven) Provides New Data about Machine L earning (A Machine Learning Approach for Estimating Snow Depth Across the Europe an Alps From Sentinel-1 Imagery)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
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. According tonews reporting originating from Leuv en, Belgium, by NewsRx correspondents, research stated, “Seasonalsnow plays a c rucial role in society and understanding trends in snow depth and mass is essent ial formaking informed decisions about water resources and adaptation to climat e change. However, quantifyingsnow depth in remote, mountainous areas with comp lex topography remains a significant challenge.”Funders for this research include KU Leuven, Belgian Federal Science Policy Offi ce, FWO, FlemishGovernment, Isis Brangers (FWO).
LeuvenBelgiumEuropeCyborgsEmergi ng TechnologiesMachine LearningUniversity of Leuven (KU Leuven)
NETL
NSTL
