首页|Findings in Support Vector Machines Reported from Military Technical College (La nd Cover Analysis of Polsar Images Using Probabilistic Voting Ensemble and Integ rated Support Vector Machine)
Findings in Support Vector Machines Reported from Military Technical College (La nd Cover Analysis of Polsar Images Using Probabilistic Voting Ensemble and Integ rated Support Vector Machine)
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 Daily News Daily News – Researchers detail new data in Support Vector Machines. According to news reporting out of Cairo, Egypt, by NewsRx edi tors, research stated, “Land cover classification is a vital application of pola rimetric synthetic aperture radar (PolSAR) images in various fields, such as agr iculture monitoring and urban assessment. We introduce a modified and enhanced P olSAR image classification method, combining six decomposition techniques, a sup port vector machine (SVM) based classifier, and a probabilistic voting ensemble (PVE) model.”
CairoEgyptAfricaEmerging Technolog iesMachine LearningSupport Vector MachinesVector MachinesMilitary Techni cal College
NETL
NSTL
