Výsledky vyhľadávania - Involution autoencoder

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  1. 1

    Involution-based efficient autoencoder for denoising histopathological images with enhanced hybrid feature extraction Autor Islam, Md. Farhadul, Reza, Md. Tanzim, Manab, Meem Arafat, Zabeen, Sarah, Islam, Md. Fahim-Ul, Shahriar, Md. Fahim, Kaykobad, Mohammad, Husna, Md. Golam Zel Asmaul, Noor, Jannatun

    ISSN: 0010-4825, 1879-0534, 1879-0534
    Vydavateľské údaje: United States Elsevier Ltd 01.06.2025
    Vydané v Computers in biology and medicine (01.06.2025)
    “…Noise in histopathology images from hardware limitations, preparation artifacts, and environmental factors complicates disease analysis and increases risks…”
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    Journal Article
  2. 2

    Involution Based Speech Autoencoder: Investigating the Advanced Vision Operator Performance on Speech Feature Extraction Autor Zhong, Tianle, Velazquez, Israel Mendoza, Haneda, Yoichi

    Vydavateľské údaje: IEEE 12.10.2021
    “… Although the involution operator has achieved great success in vision recognition, the use of the involution operator in speech tasks has not been…”
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    Konferenčný príspevok..
  3. 3

    Dynamic feature capturing in a fluid flow reduced-order model using attention-augmented autoencoders Autor Beiki, Alireza, Kamali, Reza

    ISSN: 0952-1976
    Vydavateľské údaje: Elsevier Ltd 01.06.2025
    “…This study looks into how adding adaptive attention to convolutional autoencoders can help reconstruct flow fields in fluid dynamics applications…”
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    Journal Article
  4. 4

    Style transfer with variational autoencoders is a promising approach to RNA-Seq data harmonization and analysis Autor Russkikh, Nikolai E, Antonets, Denis V, Shtokalo, Dmitry N, Makarov, Alexander V, Zakharov, Alexey M, Terentev, Evgeny V

    ISSN: 2692-8205, 2692-8205
    Vydavateľské údaje: Cold Spring Harbor Cold Spring Harbor Laboratory Press 03.10.2019
    Vydané v bioRxiv (03.10.2019)
    “…The transcriptomic data is being frequently used in the research of biomarker genes of different diseases and biological states. Generally, researchers have…”
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    Paper
  5. 5

    A concise self-adapting deep learning network for machine remaining useful life prediction Autor Xiang, Sheng, Qin, Yi, Luo, Jun, Wu, Fei, Gryllias, Konstantinos

    ISSN: 0888-3270, 1096-1216
    Vydavateľské údaje: Elsevier Ltd 15.05.2023
    “… First, a multi-branch 1D involution neural network (MINN) is proposed to adaptively extract the hidden feature from the multi-input using the involution operation, which has inverse inherence with the convolution operation…”
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    Journal Article