Výsledky vyhledávání - stacked sparse autoencoder((sage OR ssad))

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  1. 1

    Flatness pattern recognition based on stacked sparse denoising autoencoder and improved Osprey optimisation algorithm kernel-extreme learning machine Autor Zhou, Yaluo, Zhang, Shaochuan, Liu, Wenguang, Zhang, Ruicheng

    ISSN: 0301-9233, 1743-2812
    Vydáno: 11.07.2025
    Vydáno v Ironmaking & steelmaking (11.07.2025)
    “… proposes a flatness recognition method based on stack sparse denoising autoencoder (SSDAE) with improved Osprey optimisation algorithm kernel-extreme learning machine…”
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    Journal Article
  2. 2

    Stacked sparse autoencoder in cavitation noise signal data classification of hydro turbine based on power spectrum Autor Kang, Ziyang, Feng, Chi, Wan, Xiaoqing, Liu, Zhiliang, Chen, Liwei

    ISSN: 1461-3484, 2048-4046
    Vydáno: London, England SAGE Publications 01.06.2020
    “… The stacked sparse autoencoder (SSA) nuclear framework is utilized to learn more abstract and invariant high-level features from the multiple feature sets…”
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    Journal Article
  3. 3

    Image fusion based on shift invariant shearlet transform and stacked sparse autoencoder Autor Wang, Peng-Fei, Luo, Xiao-Qing, Li, Xin-Yi, Zhang, Zhan-Cheng

    ISSN: 1748-3026, 1748-3018, 1748-3026
    Vydáno: London, England SAGE Publications 01.06.2018
    “…Stacked sparse autoencoder is an efficient unsupervised feature extraction method, which has excellent ability in representation of complex data…”
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    Journal Article
  4. 4

    A deep feature extraction method for bearing fault diagnosis based on empirical mode decomposition and kernel function Autor Wang, Fengtao, Deng, Gang, Liu, Chenxi, Su, Wensheng, Han, Qingkai, Li, Hongkun

    ISSN: 1687-8132, 1687-8140, 1687-8140
    Vydáno: London, England SAGE Publications 01.09.2018
    Vydáno v Advances in mechanical engineering (01.09.2018)
    “…, which are regarded as the inputs of the proposed stacked kernel sparse autoencoder network. The proposed method does not depend on prior knowledge of fault diagnosis…”
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    Journal Article
  5. 5

    Deep Learning Role in Early Diagnosis of Prostate Cancer Autor Reda, Islam, Khalil, Ashraf, Elmogy, Mohammed, Abou El-Fetouh, Ahmed, Shalaby, Ahmed, Abou El-Ghar, Mohamed, Elmaghraby, Adel, Ghazal, Mohammed, El-Baz, Ayman

    ISSN: 1533-0346, 1533-0338, 1533-0338
    Vydáno: Los Angeles, CA SAGE Publications 01.01.2018
    “…The objective of this work is to develop a computer-aided diagnostic system for early diagnosis of prostate cancer. The presented system integrates both…”
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    Journal Article