首页|China University of Geosciences Researcher Yields New Data on Machine Learning ( Extraction of Alteration Information from Hyperspectral Data Base on Kernel Extr eme Learning Machine)
China University of Geosciences Researcher Yields New Data on Machine Learning ( Extraction of Alteration Information from Hyperspectral Data Base on Kernel Extr eme Learning 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 – Investigators discuss new findings in artificial intelligence. According to news originating from Beijing, People’s Re public of China, by NewsRx editors, the research stated, “Machine learning, as a n increasingly prominent method in recent years, has introduced new methodologie s and perspectives for extracting geological alteration information.” Our news editors obtained a quote from the research from China University of Geo sciences: “To enhance the accuracy of remote-sensing-alteration mineral informat ion, this study focuses on the extraction of alteration information from hypersp ectral remote sensing data using the Kernel-Based Extreme Learning Machine (KELM ) optimized with the Sparrow Search Algorithm (SSA). The ideal parameters of the Kernel Extreme Learning Machine model were successfully acquired by utilizing t he sparrow optimization method for continuous search and iteration, avoiding the blindness and arbitrariness associated with parameter selection by humans. Spec tral Angle Mapper (SAM) technology was used to extract sample data from hyperspe ctral imagery, which were then used to train the machine learning model for alte ration information extraction.”
China University of GeosciencesBeijingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Lear ningRemote Sensing
NETL
NSTL
