Search Results - Involution autoencoder

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  1. 1

    Involution-based efficient autoencoder for denoising histopathological images with enhanced hybrid feature extraction by 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
    Published: United States Elsevier Ltd 01.06.2025
    Published in 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 by Zhong, Tianle, Velazquez, Israel Mendoza, Haneda, Yoichi

    Published: 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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    Conference Proceeding
  3. 3

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

    ISSN: 0952-1976
    Published: 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 by Russkikh, Nikolai E, Antonets, Denis V, Shtokalo, Dmitry N, Makarov, Alexander V, Zakharov, Alexey M, Terentev, Evgeny V

    ISSN: 2692-8205, 2692-8205
    Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 03.10.2019
    Published in 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 by Xiang, Sheng, Qin, Yi, Luo, Jun, Wu, Fei, Gryllias, Konstantinos

    ISSN: 0888-3270, 1096-1216
    Published: Elsevier Ltd 15.05.2023
    Published in Mechanical systems and signal processing (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