Výsledky vyhľadávania - convolutional denoising autoencoder-convolutional neural network

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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
    Vydavateľské údaje: The Institution of Engineering and Technology 01.06.2020
    Vydané 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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    Journal Article
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    Video Analytics in Train Cabin Using Deep Learning Autor Hsien, Lur Tze, Atmosukarto, Indriyati

    Vydavateľské údaje: IEEE 01.09.2019
    “… Our proposed solution is to process extracted images from train cabin security footages using Convolutional Denoising Autoencoder-Convolutional Neural Network (CDAE-CNN…”
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    Image dehazing using autoencoder convolutional neural network Autor Singh, Richa, Dubey, Ashwani Kumar, Kapoor, Rajiv

    ISSN: 0975-6809, 0976-4348
    Vydavateľské údaje: New Delhi Springer India 01.12.2022
    “… autoencoder that compress the data using machine learning and learns through Convolutional Neural Network (CNN…”
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    A denoising semi-supervised deep learning model for remaining useful life prediction of turbofan engine degradation Autor Wang, Youming, Wang, Yue

    ISSN: 0924-669X, 1573-7497
    Vydavateľské údaje: New York Springer US 01.10.2023
    “… To address these problems, a denoised semi-supervised model based on fully convolutional denoising autoencoder, convolutional neural network, and long short-term memory network (FCDAE-CNN-LSTM…”
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    Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Denoising Autoencoder and Deep Convolutional Neural Network Autor Qu, Zhiyu, Wang, Wenyang, Hou, Changbo, Hou, Chenfan

    ISSN: 2169-3536, 2169-3536
    Vydavateľské údaje: Piscataway IEEE 2019
    Vydané v IEEE access (2019)
    “…) and deep convolutional neural network (DCNN) is proposed in this paper. First, we use Cohen's time-frequency distribution to convert radar signals into time-frequency images (TFIs…”
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    Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder Autor Jung, Yuyeon, Kim, Taewan, Han, Mi-Ryung, Kim, Sejin, Kim, Geunyoung, Lee, Seungchul, Choi, Youn Jin

    ISSN: 2045-2322, 2045-2322
    Vydavateľské údaje: London Nature Publishing Group UK 11.10.2022
    Vydané v Scientific reports (11.10.2022)
    “…Discrimination of ovarian tumors is necessary for proper treatment. In this study, we developed a convolutional neural network model with a convolutional autoencoder (CNN-CAE…”
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    PRPI-SC: an ensemble deep learning model for predicting plant lncRNA-protein interactions Autor Zhou, Haoran, Wekesa, Jael Sanyanda, Luan, Yushi, Meng, Jun

    ISSN: 1471-2105, 1471-2105
    Vydavateľské údaje: London BioMed Central 24.08.2021
    Vydané v BMC bioinformatics (24.08.2021)
    “… Results In this study, we propose an ensemble deep learning model to predict plant lncRNA-protein interactions using stacked denoising autoencoder and convolutional neural network based on sequence…”
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    Seismic Random Noise Attenuation Using a Tied-Weights Autoencoder Neural Network Autor Zhou, Huailai, Guo, Yangqin, Guo, Ke

    ISSN: 2075-163X, 2075-163X
    Vydavateľské údaje: Basel MDPI AG 01.10.2021
    Vydané v Minerals (Basel) (01.10.2021)
    “… Herein, a deep denoising convolutional autoencoder network based on self-supervised learning was developed herein to attenuate seismic random noise…”
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    Competent Ultra Data Compression By Enhanced Features Excerption Using Deep Learning Techniques Autor Nagaraj, P., Rao, J. Surendra, Muneeswaran, V., Sudheer Kumar, A., Muthamil sudar, K.

    Vydavateľské údaje: IEEE 01.05.2020
    “…%. The Convolutional LSTM model is compared with other models such as autoencoder, denoising autoencoder, convolutional neural network and our present work shows better RMSE compared to the other…”
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    Design and development of an indoor navigation system using denoising autoencoder based convolutional neural network for visually impaired people Autor Akilandeswari, J., Jothi, G., Naveenkumar, A., Sabeenian, R. S., Iyyanar, P., Paramasivam, M. E.

    ISSN: 1380-7501, 1573-7721
    Vydavateľské údaje: New York Springer US 01.01.2022
    Vydané v Multimedia tools and applications (01.01.2022)
    “… of implementation, and limitations. This paper presents a denoising auto…”
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    Intelligent fault diagnosis method of rolling bearing based on stacked denoising autoencoder and convolutional neural network Autor Che, Changchang, Wang, Huawei, Ni, Xiaomei, Fu, Qiang

    ISSN: 0036-8792, 1758-5775
    Vydavateľské údaje: Bradford Emerald Publishing Limited 17.09.2020
    Vydané v Industrial lubrication and tribology (17.09.2020)
    “…) and convolutional neural network (CNN) is proposed in this paper. The SDAE is used to process the time series data with multiple dimensions and noise interference…”
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    Journal Article
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    Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network Autor Yang, Pu, Wen, Chenwan, Geng, Huilin, Liu, Peng

    ISSN: 2075-1702, 2075-1702
    Vydavateľské údaje: Basel MDPI AG 01.12.2021
    Vydané v Machines (Basel) (01.12.2021)
    “…This paper introduces a new intelligent fault diagnosis method based on stack pruning sparse denoising autoencoder and convolutional neural network (sPSDAE-CNN…”
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    Enhancement of land-use change modeling using convolutional neural networks and convolutional denoising autoencoders Autor Du, Guodong, Liang, Yuan, Shin, Kong Joo, Managi, Shunsuke

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 03.03.2018
    Vydané v arXiv.org (03.03.2018)
    “…The neighborhood effect is a key driving factor for the land-use change (LUC) process. This study applies convolutional neural networks…”
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    Paper
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    Video surveillance image enhancement via a convolutional neural network and stacked denoising autoencoder Autor Che Aminudin, Muhamad Faris, Suandi, Shahrel Azmin

    ISSN: 0941-0643, 1433-3058
    Vydavateľské údaje: London Springer London 01.02.2022
    Vydané v Neural computing & applications (01.02.2022)
    “… To address these issues, a deep learning image enhancement (DLIE) model is proposed. By utilizing a deep learning architecture such as a convolutional neural network (CNN…”
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    Fault Diagnosis of Rolling Bearing Using Convolutional Denoising Autoencoder and Siamese Neural Network With Small Sample Autor Zhao, Xufeng, Chen, Ying, Yang, Mengshu, Xiang, Jiawei

    ISSN: 2327-4662, 2327-4662
    Vydavateľské údaje: Piscataway IEEE 01.03.2025
    Vydané v IEEE internet of things journal (01.03.2025)
    “…) the scarcity of fault data for effective diagnostic tasks in practical scenarios. To address these issues, this article proposes a novel method termed convolutional denoising autoencoder and siamese neural network (CDAE-SNN…”
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    A Robust System for Noisy Image Classification Combining Denoising Autoencoder and Convolutional Neural Network Autor Singha, Sudipta, Imran, Sk, A., M., Murase, Kazuyuki

    ISSN: 2158-107X, 2156-5570
    Vydavateľské údaje: West Yorkshire Science and Information (SAI) Organization Limited 2018
    “…) to restore original images from noisy images and then Convolutional Neural Network (CNN) is used for classification…”
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    Modulation classification based on denoising autoencoder and convolutional neural network with GNU radio Autor Wang, Jun, Wang, Wenfeng, Luo, Feixiang, Wei, Shaoming

    ISSN: 2051-3305, 2051-3305
    Vydavateľské údaje: The Institution of Engineering and Technology 01.10.2019
    “…) and convolutional neural network (CNN) is proposed. We combine denoising autoencoder's denoising ability with CNN's feature extraction capability…”
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    Condition monitoring and performance forecasting of wind turbines based on denoising autoencoder and novel convolutional neural networks Autor Jia, Xiongjie, Han, Yang, Li, Yanjun, Sang, Yichen, Zhang, Guolei

    ISSN: 2352-4847, 2352-4847
    Vydavateľské údaje: Elsevier Ltd 01.11.2021
    Vydané v Energy reports (01.11.2021)
    “… In this study, a data-driven modelling framework based on deep convolutional neural networks is constructed for wind turbines condition monitoring (CM…”
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