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Titlebook: Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health; International 2020 C Huansheng Ning,Feifei Shi Conference proceed

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发表于 2025-3-21 19:12:29 | 显示全部楼层 |阅读模式
书目名称Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health
副标题International 2020 C
编辑Huansheng Ning,Feifei Shi
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health; International 2020 C Huansheng Ning,Feifei Shi Conference proceed
描述This volume constitutes the proceedings of the Forth International Conference on Cyberspace Data and Intelligence, Cyber DI 2020, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2020, held under the umbrella of the 2020 Cyberspace Congress, held in Beijing, China, in December 2020.*.The 13 full papers presented were carefully reviewed and selected from 36 submissions. The papers are grouped in the following topics: machine learning and ubiquitous and intelligent computing...*. The conference was held virtually due to the COVID-19 pandemic..
出版日期Conference proceedings 2020
关键词architecture types; artificial intelligence; communication systems; computer vision; databases; deep lear
版次1
doihttps://doi.org/10.1007/978-981-33-4336-8
isbn_softcover978-981-33-4335-1
isbn_ebook978-981-33-4336-8Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2020
The information of publication is updating

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James Dyson,Calum Harvey-Scholesrvision is the basis for guaranteeing the productive efficiency of coal mines. The safety supervisions were previously based on handcrafted models of reality. Nowadays, they are able to be achieved using data-driven learning approaches. Hence, to improve the supervision performance in consideration
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Wolfgang Haupt,Peter Eckersley,Kristine Kernearning that trains a model for making predictions or decisions without being explicitly programmed. The computing workers in federated learning provide training for the model at the edges of network where the data are stored. Thus, they can control the data and decide whether and when participating
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Design of AAV Vectors for Delivery of RNAiof ma-chine health. In this paper, the deep learning network Variational Auto-Encoder (VAE) and Long Short-Term Memory (LSTM) network are combined to solve the health problem of the dust removal fan. The deep learning network VAE can map the features of the data to hidden variables, and the LSTM net
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Dustin J. Hines,Philip G. Haydonds on the interactions between individuals and clinical professionals. Functional magnetic resonance imaging (fMRI) has been widely used in the study of brain function in patients with ASD, which provides a new way for the diagnosis of ASD. In this paper, we propose a convolutional neural network (C
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Masahito Kawamura Jr.,David N. Ruskint of the Internet of Things are using the publish/subscribe model, which stipulates the one-to-many situation of nodes in the Internet of Things’ uses a publish/subscribe model to achieve communication, using Broker as a relay and topic as a designated transmission path to deliver information to sub
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