首页|Studies from Henan University Yield New Data on Support Vector Machines (Low-dos e Ct Image Quality Evaluation Method Based On Radiomics and Deep Residual Networ k With Attention Mechanism)
Studies from Henan University Yield New Data on Support Vector Machines (Low-dos e Ct Image Quality Evaluation Method Based On Radiomics and Deep Residual Networ k With Attention Mechanism)
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
Elsevier
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Support Vector Machines is now available. According to news reporting from Kaifeng, People’s Republic o f China, by NewsRx journalists, research stated, “Low-dose computed tomography ( CT) produces less radiation but may degrade image quality. Research on automatic evaluation and classification of low-dose CT image quality is necessary, which is helpful to clinicians.”
KaifengPeople’s Republic of ChinaAsi aEmerging TechnologiesMachine LearningSupport Vector MachinesVector Mach inesHenan University
NETL
NSTL
Elsevier
