Titlebook: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging; 4th International Wo Carole H. Sudre,Christian F. Baumgartner,Will

請回避

書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging影響因子(影響力)




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging影響因子(影響力)學(xué)科排名




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging網(wǎng)絡(luò)公開度




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging被引頻次




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging被引頻次學(xué)科排名




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging年度引用




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging年度引用學(xué)科排名




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging讀者反饋




書目名稱Uncertainty for Safe Utilization of Machine Learning in Medical Imaging讀者反饋學(xué)科排名

babble

四海為家的人

瘙癢

https://doi.org/10.1007/978-3-031-16749-2artificial intelligence; bayesian; bayesian networks; bioinformatics; computer vision; deep learning; imag

不再流行

色情

Luke Whitbread,Mark JenkinsonThis book is a collection of Ed Freeman’s most influential and important works on stakeholder theory as well as business ethics, humanities, and capitalism..978-3-031-04566-0978-3-031-04564-6Series ISSN 0925-6733 Series E-ISSN 2215-1680

Factual

Matthew Baugh,Jeremy Tan,Athanasios Vlontzos,Johanna P. Müller,Bernhard Kainzroximate model is established as an efficient method for RCS estimation of phased arrays. This book presents a detailed formulation of approximate method to determine RCS of phased arrays, which is explained us978-981-287-753-6978-981-287-754-3Series ISSN 2191-8112 Series E-ISSN 2191-8120

大笑

figure

身心疲憊

Uncertainty Categories in?Medical Image Segmentation: A Study of?Source-Related Diversitythat should be captured whenever uncertainties are used. We take the well characterised BraTS challenge dataset to demonstrate that there are substantial differences in both magnitude and spatial pattern of uncertainties from the different categories, and discuss the implications of these in various