Výsledky vyhľadávania - sparse conventional autoencoder (same)*

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  1. 1

    Masked autoencoder for highly compressed single-pixel imaging Autor Liu, Haiyan, Chang, Xuyang, Yan, Jun, Guo, Pengyu, Xu, Dong, Bian, Liheng

    ISSN: 1539-4794, 1539-4794
    Vydavateľské údaje: 15.08.2023
    Vydané v Optics letters (15.08.2023)
    “… In this way, we can effectively decrease 75% modulation patterns experimentally. To reconstruct the entire image, we designed a highly sparse input and extrapolation network consisting of two modules…”
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    Journal Article
  2. 2

    Deep learning for pixel-level image fusion: Recent advances and future prospects Autor Liu, Yu, Chen, Xun, Wang, Zengfu, Wang, Z. Jane, Ward, Rabab K., Wang, Xuesong

    ISSN: 1566-2535, 1872-6305
    Vydavateľské údaje: Elsevier B.V 01.07.2018
    Vydané v Information fusion (01.07.2018)
    “…•The difficulties that exist in conventional image fusion research are analyzed.•The advantages of deep learning (DL…”
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    Journal Article
  3. 3

    Application of the robust autoencoder to reduce reverberation and facilitate underwater target tracking Autor Xiang, Wenjie, Song, Zhongchang, Gao, Zhanyuan, Yang, Wuyi, Zhang, Boyu, Yang, Hongjun, Tu, Jianqiu, Li, Baoyu, Zhang, Hairui, Zhang, Yu

    ISSN: 0003-682X
    Vydavateľské údaje: Elsevier Ltd 15.01.2025
    Vydané v Applied acoustics (15.01.2025)
    “… To improve the accuracy of target detection under reverberation conditions, a novel sparse track-before-detect algorithm integrating a robust autoencoder and a particle filter (PF-RAE-TBD…”
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    Journal Article
  4. 4

    Seismic noise attenuation by signal reconstruction: an unsupervised machine learning approach Autor Gao, Yang, Zhao, Pingqi, Li, Guofa, Li, Hao

    ISSN: 0016-8025, 1365-2478
    Vydavateľské údaje: Houten Wiley Subscription Services, Inc 01.06.2021
    Vydané v Geophysical Prospecting (01.06.2021)
    “…ABSTRACT Random noise attenuation is an essential step in seismic data processing for improving seismic data quality and signal‐to‐noise ratio. We adopt an…”
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  5. 5

    ProteinVAE: Variational AutoEncoder for Translational Protein Design Autor Lyu, Suyue, Shahin Sowlati-Hashjin, Garton, Michael

    ISSN: 2692-8205, 2692-8205
    Vydavateľské údaje: Cold Spring Harbor Cold Spring Harbor Laboratory Press 05.03.2023
    Vydané v bioRxiv (05.03.2023)
    “… This means that they are often not suitable for generating proteins with the most potential for high clinical impact, due to the additional challenges of sparse data and large size many…”
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  6. 6

    Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments Autor Nalinipriya, G., Rama Sree, S., Radhika, K., Laxmi Lydia, E., Karim, Faten Khalid, Ishak, Mohamad Khairi, Mostafa, Samih M.

    ISSN: 2045-2322, 2045-2322
    Vydavateľské údaje: London Nature Publishing Group UK 09.07.2025
    Vydané v Scientific reports (09.07.2025)
    “… Recently, cybercriminals have become more complex with their approaches, though the underlying motives for conducting cyber threats remain largely the same…”
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  7. 7

    A new Sparse Auto-encoder based Framework using Grey Wolf Optimizer for Data Classification Problem Autor Karim, Ahmad Mozaffer

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 29.01.2022
    Vydané v arXiv.org (29.01.2022)
    “… Different training approaches are applied to train sparse autoencoders. Previous studies and preliminary experiments reveal that those approaches may present remarkable…”
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  8. 8

    On the Performance of Deep Learning-based Data-aided Active User Detection for GF-SCMA System Autor Han, Minsig, Abebet, Ameha T., Kang, Chung G.

    Vydavateľské údaje: IEEE 19.10.2022
    “…) in the receiver has demonstrated a significant performance improvement for grant-free sparse code multiple access (GF-SCMA) system…”
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  9. 9

    On the Performance of Deep Learning-based Data-aided Active User Detection for GF-SCMA System Autor Han, Minsig, Ameha Tsegaye Abebe, Kang, Chung G

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 05.09.2022
    Vydané v arXiv.org (05.09.2022)
    “…) in the receiver has demonstrated a significant performance improvement for grant-free sparse code multiple access (GF-SCMA) system…”
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  10. 10

    A dense multi-path decoder for tissue segmentation in histopathology images Autor Vu, Quoc Dang, Kwak, Jin Tae

    ISSN: 0169-2607, 1872-7565, 1872-7565
    Vydavateľské údaje: Ireland Elsevier B.V 01.05.2019
    “…•We propose a dense multi-path decoder for tissue segmentation in histopathology images.•Convolutional neural networks are built upon the up-to-date encoders…”
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