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中兴通讯技术（英文版）
中兴通讯技术（英文版）

谢大雄

季刊

1673-5188

magazine@zte.com.cn

0551-5533356

230061

合肥市金寨路329号凯旋大厦1201室

中兴通讯技术（英文版）/Journal ZTE Communications
查看更多>>ZTE　Communications is a quarterly publication, edited, published and distributed by the Corporate Branding and Communications Department of ZTE Corporation. The magazine focuses on hot telecom topics and front-line telecom technologies, with the sections of “Special Topic”, “Operational Application”, “Research Paper”, “Development Field” and “Lecture Series”. It is a worthwhile magazine for telecom operators and partners of ZTE Corporation alike. The magazine is mainly distributed to telecom operators, science and technology research institutes, relevant government departments, and colleges and universities.
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    Video Enhancement Network Based on CNN and Transformer

    YUAN LangHUI ChenWU YanfengLIAO Ronghua...
    78-88页
    查看更多>>摘要：To enhance the video quality after encoding and decoding in video compression,a video quality enhancement framework is pro-posed based on local and non-local priors in this paper. Low-level features are first extracted through a single convolution layer and then pro-cessed by several conv-tran blocks (CTB) to extract high-level features,which are ultimately transformed into a residual image. The final re-constructed video frame is obtained by performing an element-wise addition of the residual image and the original lossy video frame. Experi-ments show that the proposed Conv-Tran Network (CTN) model effectively recovers the quality loss caused by Versatile Video Coding (VVC) and further improves VVC's performance.
      原文链接:
    • 万方数据
    • 维普

    A Privacy-Preserving Scheme for Multi-Party Vertical Federated Learning

    FAN MochanZHANG ZhipengLI DifeiZHANG Qiming...
    89-96页
    查看更多>>摘要：As an important branch of federated learning,vertical federated learning (VFL) enables multiple institutions to train on the same user samples,bringing considerable industry benefits. However,VFL needs to exchange user features among multiple institutions,which raises concerns about privacy leakage. Moreover,existing multi-party VFL privacy-preserving schemes suffer from issues such as poor reli-ability and high communication overhead. To address these issues,we propose a privacy protection scheme for four institutional VFLs,named FVFL. A hierarchical framework is first introduced to support federated training among four institutions. We also design a verifiable repli-cated secret sharing (RSS) protocol (32)-sharing and combine it with homomorphic encryption to ensure the reliability of FVFL while ensuring the privacy of features and intermediate results of the four institutions. Our theoretical analysis proves the reliability and security of the pro-posed FVFL. Extended experiments verify that the proposed scheme achieves excellent performance with a low communication overhead.
      原文链接:
    • 万方数据
    • 维普

    ZTE Communications Table of Contents,Volume 22,2024

    后插1-后插2页
      原文链接:
    • 万方数据