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Communications, Networking, and Information Systems: First International Congress, CNIS 2023, Guilin, China, March 25–27, 2023, Revised Selected Papers de Haonan Chen

Communications, Networking, and Information Systems: First International Congress, CNIS 2023, Guilin, China, March 25–27, 2023, Revised Selected Papers: Communications in Computer and Information Science, cartea 1839

Editat de Haonan Chen, Pingyi Fan, Lipo Wang
en Limba Engleză Paperback – 9 iun 2023
This volume constitutes selected papers presented at the First International Congress on Communications, Networking, and Information Systems, CNIS 2023, held in Guilin, China, in March 2023. 

The 8 full papers and 2 short papers presented were thoroughly reviewed and selected from the 32 submissions. The papers are organized in topical sections on ​communications and networking, and information systems and artificial intelligence.
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Specificații

ISBN-13: 9789819935802
ISBN-10: 9819935806
Ilustrații: XII, 173 p. 72 illus., 62 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.27 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Singapore, Singapore

Cuprins

Communications and Networking.- Deep reinforcement learning based vehicle selection for asynchronous federated learning enabled vehicular edge computing.- A Virtual Community Healthcare Framework in Metaverse Enabled by Digital Twins.- An improved LED aruco-marker detection method for event camera.- Improvement Of CenterNet Based On Feature Pyramid Networks.- Information Security Protection Techniques for Substation Operation and Maintenance Edge Gateway.- A Robust MOR-Based Secure Fusion Strategy against Byzantine Attack in Cooperative Spectrum Sensing.- Security Analysis of Blockchain Layer-one Sharding based Extended-UTxO Model.- Information Systems and Artificial Intelligence.- Fundamental Frequency Removal PCA Method and SVM Approach Used for Structure Feature Distilling and Damage Diagnosis.- Stock trend prediction based on improved SVR.- Several Misconceptions and Misuses of Deep Neural Networks and Deep Learning.