Cyberspace data and intelligence, an...
International Conference on Cyberspace Data and Intelligence (2020 :)

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  • Cyberspace data and intelligence, and cyber-living, syndrome, and health = International 2020 Cyberspace Congress, CyberDI/CyberLife 2020, Beijing, China, December 10-12, 2020 : proceedings /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Cyberspace data and intelligence, and cyber-living, syndrome, and health/ edited by Huansheng Ning, Feifei Shi.
    Reminder of title: International 2020 Cyberspace Congress, CyberDI/CyberLife 2020, Beijing, China, December 10-12, 2020 : proceedings /
    remainder title: CyberDI/CyberLife 2020
    other author: Ning, Huansheng.
    corporate name: International Conference on Cyberspace Data and Intelligence
    Published: Singapore :Springer Singapore : : 2020.,
    Description: xii, 163 p. :ill., digital ;24 cm.
    [NT 15003449]: Machine Learning -- Safety Supervision for Coal Mines Using Machine Learning Methods -- Iterative Optimization for Edge Federated Learning -- Machinery Health Prognostics of Dust Removal Fan Data through Deep Neural Networks -- Numeric CNNs: CNNs for Reading Numeric Characters on Meters -- DeepTSW: An Urban Traffic Safety Warning Framework based on Bayesian Deep Learning -- A Multimodal Semantic Model of Packaging Sorting Field Based on Deep Learning -- Classification of Autism based on fMRI Data with Feature-fused Convolutional Neural Network -- Ubiquitous and Intelligent Computing -- Topic Logistics Based on Node Resource Status -- Summarization of Coal Mine Accident Reports: A Natural-Language-Processing-Based Approach -- The College Student Credit Evaluation based on Characteristic Data -- Research on Human Pose Estimation and Object Detection in the Field of Unmanned Retail -- Edge Computing-based Solution and Framework for Software-Defined Industrial Intelligent Control in Industrial Internet of Things -- Wi-Sector - A Novel Sector-based WiFi Scheduling.
    Contained By: Springer Nature eBook
    Subject: Machine learning - Congresses. -
    Online resource: https://doi.org/10.1007/978-981-33-4336-8
    ISBN: 9789813343368
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