日冕物质抛射(Coronal Mass Ejection,CME)的检测是建立CME事件库和实现对CME在行星际传播的预报的重要前提.通过Visual Geometry Group(VGG)16卷积神经网络方法对日冕仪图像进行自动分类.基于大角度光谱日冕仪(Large Angle and Spectro...
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日冕物质抛射(Coronal Mass Ejection,CME)的检测是建立CME事件库和实现对CME在行星际传播的预报的重要前提.通过Visual Geometry Group(VGG)16卷积神经网络方法对日冕仪图像进行自动分类.基于大角度光谱日冕仪(Large Angle and Spectrometric Coronagraph Experiment,LASCO)C2的白光日冕仪图像,根据是否观测到CME对图像进行标记.将标记分类的数据集用于VGG模型的训练,该模型在测试集分类的准确率达到92.5%.根据检测得到的标签结果,结合时空连续性规则,消除了误判区域,有效分类出CME图像序列.与Coordinated Data Analysis Workshops(CDAW)人工事件库比较,分类出的CME图像序列能够较完整地包含CME事件,且对弱CME结构有较高的检测灵敏度.未来先进天基太阳天文台(Advanced Space-based Solar Observatory,ASO-S)卫星的莱曼阿尔法太阳望远镜将搭载有白光日冕仪(Solar Corona Imager,SCI),使用此分类方法将该仪器产生的日冕图像按有无CME分类.含CME标签的图像将推送给中国的各空间天气预报中心,对CME进行预警.
Medical imaging is now being reshaped by artificial intelligence (AI) and progressing rapidly toward *** this article,we review the recent progress of AI-enabled medical ***,we briefly review the background about AI i...
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Medical imaging is now being reshaped by artificial intelligence (AI) and progressing rapidly toward *** this article,we review the recent progress of AI-enabled medical ***,we briefly review the background about AI in its way of ***,we discuss the recent successes of AI in different medical imaging tasks,especially in image segmentation,registration,detection and ***,we illustrate several representative applications of AI-enabled medical imaging to show its advantage in real scenario,which includes lung nodule in chest CT,neuroimaging,mammography,and ***,we report the way of human-machine *** believe that,in the future,AI will not only change the traditional way of medical imaging,but also improve the clinical routines of medical care and enable many aspects of the medical society.
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