Výsledky vyhledávání - "denoising autoencoder network"

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  1. 1

    Deep frequency-recurrent priors for inverse imaging reconstruction Autor He, Zhuonan, Hong, Kai, Zhou, Jinjie, Liang, Dong, Wang, Yuhao, Liu, Qiegen

    ISSN: 0165-1684, 1872-7557
    Vydáno: Elsevier B.V 01.01.2022
    Vydáno v Signal processing (01.01.2022)
    “…•A multi-profile high-frequency transform-guided denoising autoencoder for attainting deep frequency recurrent prior.•We extract a set of multi-profile…”
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  2. 2

    Multi-Channel and Multi-Model-Based Autoencoding Prior for Grayscale Image Restoration Autor Li, Sanqian, Qin, Binjie, Xiao, Jing, Liu, Qiegen, Wang, Yuhao, Liang, Dong

    ISSN: 1057-7149, 1941-0042, 1941-0042
    Vydáno: United States IEEE 01.01.2020
    Vydáno v IEEE transactions on image processing (01.01.2020)
    “…Image restoration (IR) is a long-standing challenging problem in low-level image processing. It is of utmost importance to learn good image priors for pursuing…”
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  3. 3

    Wind turbine generator early fault diagnosis using LSTM-based stacked denoising autoencoder network and stacking algorithm Autor Yan, Junshuai, Liu, Yongqian, Meng, Hang, Li, Li, Ren, Xiaoying

    ISSN: 1543-5075, 1543-5083, 1543-5083
    Vydáno: Taylor & Francis 01.09.2024
    Vydáno v International journal of green energy (01.09.2024)
    “…To reduce the significant economic losses caused by the fault deterioration of wind turbine generators, it is urgent to detect and diagnose the early faults of…”
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  4. 4

    A Novel PAPR Reduction Scheme Based on Deep Autoencoder Network for FBMC Systems Autor Cheng, Xing, Chen, Deli, Li, Shuaishuai, He, Shanbao, Kong, Dejin

    ISSN: 2169-3536, 2169-3536
    Vydáno: Piscataway IEEE 2025
    Vydáno v IEEE access (2025)
    “…Filter bank multicarrier (FBMC) is a crucial complementary waveform to orthogonal frequency-division multiplexing (OFDM) in future communication systems…”
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  5. 5

    自编码网络在JavaScript恶意代码检测中的应用研究 Autor 龙廷艳, 万良, 丁红卫

    ISSN: 1673-9418
    Vydáno: 贵州大学 计算机软件与理论研究所,贵阳 550025 01.12.2019
    Vydáno v 计算机科学与探索 (01.12.2019)
    “…TP391; 针对传统机器学习特征提取方法很难发掘JavaScript恶意代码深层次本质特征的问题,提出基于堆栈式稀疏降噪自编码网络(sSDAN)的JavaScript恶意代码检测方法.首先…”
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