首页|Study Results from Texas Tech University Broaden Understanding of Machine Learni ng (Ensemble Machine Learning on the Fusion of Sentinel Time Series Imagery with High-Resolution Orthoimagery for Improved Land Use/Land Cover Mapping)
Study Results from Texas Tech University Broaden Understanding of Machine Learni ng (Ensemble Machine Learning on the Fusion of Sentinel Time Series Imagery with High-Resolution Orthoimagery for Improved Land Use/Land Cover Mapping)
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 – Current study results on artificial in telligence have been published. According to newsoriginating from Lubbock, Texa s, by NewsRx editors, the research stated, “In the United States, severalland u se and land cover (LULC) data sets are available based on satellite data, but th ese data setsoften fail to accurately represent features on the ground. Alterna tively, detailed mapping of heterogeneouslandscapes for informed decision-makin g is possible using high spatial resolution orthoimagery from theNational Agric ultural Imagery Program (NAIP).”
Texas Tech UniversityLubbockTexasU nited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
