Výsledky vyhledávání - convolutional autoencoder network

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  1. 1

    Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial–temporal features extraction Autor D’Angelo, Gianni, Palmieri, Francesco

    ISSN: 1084-8045, 1095-8592
    Vydáno: Elsevier Ltd 01.01.2021
    “… For this purpose, a novel autoencoder-based deep neural network architecture…”
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    CNNDLP: A Method Based on Convolutional Autoencoder and Convolutional Neural Network with Adjacent Edge Attention for Predicting lncRNA–Disease Associations Autor Xuan, Ping, Sheng, Nan, Zhang, Tiangang, Liu, Yong, Guo, Yahong

    ISSN: 1422-0067, 1661-6596, 1422-0067
    Vydáno: Switzerland MDPI AG 30.08.2019
    “…-source data and to learn the low-dimensional feature representations from these data. We propose a method based on the convolutional neural network with the attention…”
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    Advancements in Gas Turbine Fault Detection: A Machine Learning Approach Based on the Temporal Convolutional NetworkAutoencoder Model Autor Fahmi, Al-Tekreeti Watban Khalid, Reza Kashyzadeh, Kazem, Ghorbani, Siamak

    ISSN: 2076-3417, 2076-3417
    Vydáno: Basel MDPI AG 01.06.2024
    Vydáno v Applied sciences (01.06.2024)
    “… For this purpose, an advanced Temporal Convolutional Network (TCN)–Autoencoder model was presented to detect anomalies in vibration data…”
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  4. 4

    Plant disease detection using hybrid model based on convolutional autoencoder and convolutional neural network Autor Bedi, Punam, Gole, Pushkar

    ISSN: 2589-7217, 2589-7217
    Vydáno: Elsevier B.V 2021
    “… This paper proposes a novel hybrid model based on Convolutional Autoencoder (CAE) network and Convolutional Neural Network (CNN…”
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  5. 5

    Predicting transonic flowfields in non–homogeneous unstructured grids using autoencoder graph convolutional networks Autor Immordino, Gabriele, Vaiuso, Andrea, Da Ronch, Andrea, Righi, Marcello

    ISSN: 0021-9991
    Vydáno: Elsevier Inc 01.03.2025
    Vydáno v Journal of computational physics (01.03.2025)
    “… Our approach leverages geometric deep learning, specifically through the use of an autoencoder architecture built on graph convolutional networks…”
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    An Elliptic Kernel Unsupervised Autoencoder-Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing Autor Alfaro-Mejia, Estefania, Delgado, Carlos J., Manian, Vidya

    ISSN: 1939-1404, 2151-1535
    Vydáno: Piscataway IEEE 2025
    “… In the initial stage, endmember extraction and abundance map estimation are carried out using a convolutional autoencoder…”
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  7. 7

    Segmentation of digital rock images using deep convolutional autoencoder networks Autor Karimpouli, Sadegh, Tahmasebi, Pejman

    ISSN: 0098-3004
    Vydáno: Elsevier Ltd 01.05.2019
    Vydáno v Computers & geosciences (01.05.2019)
    “…). Among them, convolutional autoencoder networks have produced accurate results in different applications when various images are available for the training…”
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    Early Parkinson's Disease Prediction Using rS-fMRI Functional Connectivity and Autoencoder Graph Convolutional Network Autor Limas, Lesbia Lopez, Manian, Vidya

    ISSN: 2169-3536, 2169-3536
    Vydáno: Piscataway IEEE 2025
    Vydáno v IEEE access (2025)
    “… We propose a deep learning framework that combines resting-state functional MRI (rs-fMRI) data and a Graph Convolutional Network (GCN…”
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    Multi-stage convolutional autoencoder network for hyperspectral unmixing Autor Yu, Yang, Ma, Yong, Mei, Xiaoguang, Fan, Fan, Huang, Jun, Li, Hao

    ISSN: 1569-8432, 1872-826X
    Vydáno: Elsevier B.V 01.09.2022
    “… Among the various linear unmixing methods, the autoencoder unmixing network has achieved superior performance and presented more significant potential because of the powerful data fitting ability…”
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    Multi-level convolutional autoencoder networks for parametric prediction of spatio-temporal dynamics Autor Xu, Jiayang, Duraisamy, Karthik

    ISSN: 0045-7825, 1879-2138
    Vydáno: Amsterdam Elsevier B.V 01.12.2020
    “… A convolutional autoencoder is used as the top level to encode the high dimensional input data along spatial dimensions into a sequence of latent variables…”
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    CAE-CNN: Predicting transcription factor binding site with convolutional autoencoder and convolutional neural network Autor Zhang, Yongqing, Qiao, Shaojie, Zeng, Yuanqi, Gao, Dongrui, Han, Nan, Zhou, Jiliu

    ISSN: 0957-4174, 1873-6793
    Vydáno: New York Elsevier Ltd 30.11.2021
    Vydáno v Expert systems with applications (30.11.2021)
    “…•Integrate the unsupervised and supervised method to predict the TF binding site.•CAE-CNN share the parameters, so the training time can be significantly…”
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  12. 12

    Anomaly Detection Based on Graph Convolutional Network–Variational Autoencoder Model Using Time-Series Vibration and Current Data Autor Choi, Seung-Hwan, An, Dawn, Lee, Inho, Lee, Suwoong

    ISSN: 2227-7390, 2227-7390
    Vydáno: Basel MDPI AG 01.12.2024
    Vydáno v Mathematics (Basel) (01.12.2024)
    “…This paper proposes a deep learning-based anomaly detection method using time-series vibration and current data, which were obtained from endurance tests on…”
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    CAD-Skin: A Hybrid Convolutional Neural NetworkAutoencoder Framework for Precise Detection and Classification of Skin Lesions and Cancer Autor Khan, Abdullah, Sajid, Muhammad Zaheer, Khan, Nauman Ali, Youssef, Ayman, Abbas, Qaisar

    ISSN: 2306-5354, 2306-5354
    Vydáno: Switzerland MDPI AG 21.03.2025
    Vydáno v Bioengineering (Basel) (21.03.2025)
    “… neural networks and autoencoders to improve the classification efficiency of skin cancer…”
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    Convolutional autoencoder network lithology recognition based on scratch tests Autor Wang, Suling, Ren, Zhihui, Dong, Kangxing, Li, Yanchun, Li, Jinbo, Wen, Pengyun, Qu, Ruyi, Li, Tingting, Wen, Zhennan

    ISSN: 2045-2322, 2045-2322
    Vydáno: London Nature Publishing Group UK 19.08.2025
    Vydáno v Scientific reports (19.08.2025)
    “… By integrating convolutional neural network (CNN) and auto-encode network (AE), a novel lithology identification method based on scratch data was proposed…”
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    Extract features from lithium-ion battery electrochemical impedance spectra and estimate state of health based on improved convolutional autoencoder-temporal convolutional network Autor Lou, Cheng, Wang, Shi, Li, Zhaoting, Wang, Kai

    ISSN: 0947-7047, 1862-0760
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2025
    Vydáno v Ionics (01.05.2025)
    “… into a two-dimensional image format. We have developed an improved convolutional autoencoder (ICAE…”
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    Single-pixel imaging with untrained convolutional autoencoder network Autor Li, Zhicai, Huang, Jian, Shi, Dongfeng, Chen, Yafeng, Yuan, Kee, Hu, Shunxing, Wang, Yingjian

    ISSN: 0030-3992, 1879-2545
    Vydáno: Elsevier Ltd 01.12.2023
    Vydáno v Optics and laser technology (01.12.2023)
    “…•We propose a physical model-driven untrained deep convolutional autoencoder network for SPI and validate its performance from simulations and experiments…”
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    Bayesian optimization and channel-fusion-based convolutional autoencoder network for fault diagnosis of rotating machinery Autor Zou, L., Zhuang, K.J., Zhou, A., Hu, J.

    ISSN: 0141-0296, 1873-7323
    Vydáno: Elsevier Ltd 01.04.2023
    Vydáno v Engineering structures (01.04.2023)
    “…•A novel convolutional network based on Bayesian optimization and channel fusion mechanism is developed…”
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    Within-project and cross-project just-in-time defect prediction based on denoising autoencoder and convolutional neural network Autor Zhu, Kun, Zhang, Nana, Ying, Shi, Zhu, Dandan

    ISSN: 1751-8806, 1751-8814, 1751-8814
    Vydáno: The Institution of Engineering and Technology 01.06.2020
    Vydáno v IET software (01.06.2020)
    “… Therefore, the authors propose a novel just-in-time defect prediction model named DAECNN-JDP based on denoising autoencoder and convolutional neural network in this study, which has three main advantages…”
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    Indoor Localization with an Autoencoder based Convolutional Neural Network Autor Arslantas, Hatice, Okdem, Selcuk

    ISSN: 2169-3536, 2169-3536
    Vydáno: Piscataway IEEE 01.01.2024
    Vydáno v IEEE access (01.01.2024)
    “… In this study, we propose a method and training strategy that is entirely based on a Convolutional Neural Network (CNN…”
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