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Titlebook: Dependability in Sensor, Cloud, and Big Data Systems and Applications; 5th International Co Guojun Wang,Md Zakirul Alam Bhuiyan,Yizhi Ren C

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发表于 2025-3-21 16:15:14 | 显示全部楼层 |阅读模式
书目名称Dependability in Sensor, Cloud, and Big Data Systems and Applications
副标题5th International Co
编辑Guojun Wang,Md Zakirul Alam Bhuiyan,Yizhi Ren
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Dependability in Sensor, Cloud, and Big Data Systems and Applications; 5th International Co Guojun Wang,Md Zakirul Alam Bhuiyan,Yizhi Ren C
描述This book constitutes the refereed proceedings of the 5th International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications, DependSys, held in Guangzhou, China, in November 2019..The volume presents 39 full papers, which were carefully reviewed and selected from 112 submissions. The papers are organized in topical sections on ​dependability and security fundamentals and technologies; dependable and secure systems; dependable and secure applications; dependability and security measures and assessments; explainable artificial inteligence for cyberspace..
出版日期Conference proceedings 2019
关键词artificial intelligence; computer network; computer security; data communication systems; data mining; da
版次1
doihttps://doi.org/10.1007/978-981-15-1304-6
isbn_softcover978-981-15-1303-9
isbn_ebook978-981-15-1304-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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Magnetic Resonance Microscopy AT9.4 Tesla,pository. We use the trained models to predict whether a mail is spam or not, and find better prediction scheme by comparing quantitative results. The experimental results show that the method of decision forest regression can get better performance and is suitable for numerical prediction.
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Language and the emergence of environment the surprising shapes in restorative images preparing. To improve the exhibition of our proposed procedure we utilize the artificial bee colony to optimize and classify the feature selected or extracted by the WPD. Results shows that our method perform better to segment the curvy shapes and haemorrhagic areas in MRI images.
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Dwelling, Place and Environment from video sequences; (2) feature creation, where body features are constructed using body keypoints; and (3) classifier selection when such data are used to train four different classifiers in order to determine the one that best performs. The results are analyzed on the dataset Gotcha, characterized by user and camera either in motion.
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A Comparative Study of Two Different Spam Detection Methodspository. We use the trained models to predict whether a mail is spam or not, and find better prediction scheme by comparing quantitative results. The experimental results show that the method of decision forest regression can get better performance and is suitable for numerical prediction.
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