首页|Studies from Chinese Academy of Sciences Reveal New Findings on Kernal Learning (Nsckl: Normalized Spectral Clustering With Kernel-based Learning for Semisuperv ised Hyperspectral Image Classification)
Studies from Chinese Academy of Sciences Reveal New Findings on Kernal Learning (Nsckl: Normalized Spectral Clustering With Kernel-based Learning for Semisuperv ised Hyperspectral Image Classification)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Kernal Learning is now available. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Spatial-spectral classification (SSC) has become a trend for hyperspectral image (HSI) classification. However, most S SC methods mainly consider local information, so that some correlations may not be effectively discovered when they appear in regions that are not contiguous.” Funders for this research include National Natural Science Foundation of China ( NSFC), European Union’s Horizon Research, Scientific Research Program of the Edu cation Department of Shaanxi Province, Scientific Research Foundation of Xi’an U niversity of Science and Technology.
BeijingPeople’s Republic of ChinaAsi aKernal LearningEmerging TechnologiesKernel Based LearningMachine Learni ngChinese Academy of Sciences
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NSTL
