Výsledky vyhledávání - Stack autoencoder~

  1. 1

    Fault Diagnosis of Rolling Bearings Based on an Improved Stack Autoencoder and Support Vector Machine Autor Cui, Mingliang, Wang, Youqing, Lin, Xinshuang, Zhong, Maiying

    ISSN: 1530-437X, 1558-1748
    Vydáno: New York IEEE 15.02.2021
    Vydáno v IEEE sensors journal (15.02.2021)
    “… To solve this issue, this study proposes a feature distance stack autoencoder (FD-SAE) for rolling bearing fault diagnosis…”
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    Journal Article
  2. 2

    Stack Autoencoder Transfer Learning Algorithm for Bearing Fault Diagnosis Based on Class Separation and Domain Fusion Autor Sun, Meidi, Wang, Hui, Liu, Ping, Huang, Shoudao, Wang, Pan, Meng, Jinhao

    ISSN: 0278-0046, 1557-9948
    Vydáno: New York IEEE 01.03.2022
    “… In this article, we propose a stack autoencoder transfer learning algorithm based on the class separation and domain fusion (SAE-CSDF…”
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  3. 3

    Epileptic Seizure Recognition Using Reduced Deep Convolutional Stack Autoencoder and Improved Kernel RVFLN From EEG Signals Autor Sahani, Mrutyunjaya, Rout, Susanta Kumar, Dash, Pradipta Kishor

    ISSN: 1932-4545, 1940-9990, 1940-9990
    Vydáno: New York IEEE 01.06.2021
    “…In this paper, reduced deep convolutional stack autoencoder (RDCSAE) and improved kernel random vector functional link network (IKRVFLN…”
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  4. 4

    Vehicle type classification using graph ant colony optimizer based stack autoencoder model Autor Rani, B. Kavitha, Rao, M. Varaprasad, Patra, Raj Kumar, Srinivas, K., Madhukar, G.

    ISSN: 1380-7501, 1573-7721
    Vydáno: New York Springer US 01.12.2022
    Vydáno v Multimedia tools and applications (01.12.2022)
    “…In the intelligent transport system, vehicle type classification technology plays a major role. With the growth of video processing and pattern recognition…”
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  5. 5

    Deep Convolutional Stack Autoencoder of Process Adaptive VMD Data With Robust Multikernel RVFLN for Power Quality Events Recognition Autor Sahani, Mrutyunjaya, Dash, Pradipta Kishore

    ISSN: 0018-9456, 1557-9662
    Vydáno: New York IEEE 2021
    “…). A novel reduced deep convolutional neural network (RDCNN) embedded with stack autoencoder, that is, RDCSAE structure is introduced to extract the most discriminative…”
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  6. 6

    Precise single step and multistep short-term photovoltaic parameters forecasting based on reduced deep convolutional stack autoencoder and minimum variance multikernel random vector functional network Autor Sahani, Mrutyunjaya, Choudhury, Sasmita, Siddique, Marif Daula, Parida, Tanmoy, Dash, Pradipta Kishore, Panda, Sanjib Kumar

    ISSN: 0952-1976
    Vydáno: Elsevier Ltd 01.10.2024
    “… To address this, we have developed a novel hybrid model: a reduced deep convolutional stack autoencoder with a minimum variance multikernel random vector functional link network (RDCSAE-MVMRVFLN…”
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  7. 7

    A Just-in-Time Fine-Tuning Framework for Deep Learning of SAE in Adaptive Data-Driven Modeling of Time-Varying Industrial Processes Autor Wu, Yijun, Liu, Diju, Yuan, Xiaofeng, Wang, Yalin

    ISSN: 1530-437X, 1558-1748
    Vydáno: New York IEEE 01.02.2021
    Vydáno v IEEE sensors journal (01.02.2021)
    “… This may cause their performance degradation in time-varying processes. To deal with this problem, an adaptive updating framework is proposed for deep learning, which is based on just-in-time fine-tuning of stacked autoencoder (JIT-SAE…”
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  8. 8

    Damage assessments of composite under the environment with strong noise based on synchrosqueezing wavelet transform and stack autoencoder algorithm Autor Su, Chenhui, Jiang, Mingshun, Liang, Jianying, Tian, Aiqin, Sun, Lin, Zhang, Lei, Zhang, Faye, Sui, Qingmei

    ISSN: 0263-2241, 1873-412X
    Vydáno: London Elsevier Ltd 01.05.2020
    “… This study proposes a technique for damage location and quantitative identification for composites under strong noise background on the basis of synchro squeezing wavelet transform and stack autoencoder algorithm…”
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  9. 9

    SDCA: a novel stack deep convolutional autoencoder – an application on retinal image denoising Autor Ghosh, Swarup Kr, Biswas, Biswajit, Ghosh, Anupam

    ISSN: 1751-9659, 1751-9667
    Vydáno: The Institution of Engineering and Technology 12.12.2019
    Vydáno v IET image processing (12.12.2019)
    “… This study represents a deep learning based approach to denoising images and restoring features using stack denoising convolutional autoencoder…”
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  10. 10

    Application of deep stack autoencoder network in ship weight estimation Autor CHEN Jian,TANG Junyao,ZHU Shengguang,ZHOU Zhaozhao

    ISSN: 1000-3428
    Vydáno: Editorial Office of Computer Engineering 01.05.2019
    Vydáno v Ji suan ji gong cheng (01.05.2019)
    “… the parameters.The deep stack autoencoder network is used to mine the deep data features and do analysis on the ShipWE self-built…”
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  11. 11

    Classification method for imbalanced LiDAR point cloud based on stack autoencoder Autor Ren, Peng, Xia, Qunli

    ISSN: 2688-1594, 2688-1594
    Vydáno: AIMS Press 01.01.2023
    Vydáno v Electronic research archive (01.01.2023)
    “… Therefore, by studying the existing deep network structure and imbalanced sampling methods, this paper proposes an oversampling method based on stack autoencoder…”
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  12. 12

    Electricity theft detection based on stacked sparse denoising autoencoder Autor Huang, Yifan, Xu, Qifeng

    ISSN: 0142-0615, 1879-3517
    Vydáno: Elsevier Ltd 01.02.2021
    “…Inspired by the powerful feature extraction and the data reconstruction ability of autoencoder, a stacked sparse denoising autoencoder is developed for electricity theft detection in this paper…”
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  13. 13

    A new Stack Autoencoder: Neighbouring Sample Envelope Embedded Stack Autoencoder Ensemble Model Autor Zhou, Chuanyan, Ma, Jie, Li, Fan, Li, Yongming, Wang, Pin, Zhang, Xiaoheng

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 25.10.2022
    Vydáno v arXiv.org (25.10.2022)
    “…Stack autoencoder (SAE), as a representative deep network, has unique and excellent performance in feature learning, and has received extensive attention from researchers…”
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    Paper
  14. 14

    Stacked Autoencoders Driven by Semi-Supervised Learning for Building Extraction from near Infrared Remote Sensing Imagery Autor Protopapadakis, Eftychios, Doulamis, Anastasios, Doulamis, Nikolaos, Maltezos, Evangelos

    ISSN: 2072-4292, 2072-4292
    Vydáno: MDPI AG 01.02.2021
    Vydáno v Remote sensing (Basel, Switzerland) (01.02.2021)
    “…In this paper, we propose a Stack Auto-encoder (SAE)-Driven and Semi-Supervised (SSL)-Based Deep Neural Network…”
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  15. 15

    Fault diagnosis of brushless DC motor based on Stack Sparse Autoencoder Autor Du, Qiang, Zhu, Danjiang, Ni, Ming

    ISSN: 1742-6588, 1742-6596
    Vydáno: Bristol IOP Publishing 01.12.2023
    Vydáno v Journal of physics. Conference series (01.12.2023)
    “…Because of their simple structure, long service life, high efficiency, etc., brushless DC (BLDC) motors have been widely applied in many fields. In some…”
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  16. 16

    BePCon: A Photoplethysmography-based Quality-aware Continuous Beat-to-Beat Blood Pressure Measurement Technique Using Deep Learning Autor Roy, Monalisa Singha, Gupta, Rajarshi, Sharma, Kaushik Das

    ISSN: 0018-9456, 1557-9662
    Vydáno: New York IEEE 2022
    “…). Initially, the signal quality assessment (SQA) of PPG is done by a self-organizing map (SOM). Next, the time-domain, statistical, wavelet and stacked autoencoder features from current and previous good quality PPG cycles are extracted…”
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  17. 17

    SAE+LSTM: A New Framework for Emotion Recognition From Multi-Channel EEG Autor Xing, Xiaofen, Li, Zhenqi, Xu, Tianyuan, Shu, Lin, Hu, Bin, Xu, Xiangmin

    ISSN: 1662-5218, 1662-5218
    Vydáno: Switzerland Frontiers Research Foundation 12.06.2019
    Vydáno v Frontiers in neurorobotics (12.06.2019)
    “… Specially, Stack AutoEncoder (SAE) is used to build and solve the linear EEG mixing model and the emotion timing model is based on the Long Short-Term Memory Recurrent Neural Network (LSTM-RNN…”
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  18. 18

    Research on HRRP target recognition based on one-dimensional stack convolutional autoencoder Autor Zhang, Guoling, Wang, Xiaodan, Li, Rui, Lai, Jie, Xiang, Qian

    ISSN: 1742-6588, 1742-6596
    Vydáno: Bristol IOP Publishing 01.11.2020
    Vydáno v Journal of physics. Conference series (01.11.2020)
    “… Aiming at the problem of feature extraction and recognition in HRRP target recognition, a one-dimensional stack convolutional autoencoder (1D-sCAE…”
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  19. 19

    SDAE-LFM: A Latent Factor Model for Recommendation Based on Stack Denoising AutoEncoder Autor Luo, Jianyan, Xing, Xing, Zheng, Hang, Xin, Mindong, Jia, Zhichun

    ISSN: 1742-6588, 1742-6596
    Vydáno: Bristol IOP Publishing 01.09.2020
    Vydáno v Journal of physics. Conference series (01.09.2020)
    “… In order to deal with these problems, we proposed a latent factor model recommendation algorithm based on stack denoising autoencoder (SDAE-LFM…”
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  20. 20

    Damage characterization using CNN and SAE of broadband Lamb waves Autor Gao, Fei, Hua, Jiadong

    ISSN: 0041-624X, 1874-9968, 1874-9968
    Vydáno: Elsevier B.V 01.02.2022
    Vydáno v Ultrasonics (01.02.2022)
    “…) and stack autoencoder (SAE) are promising to extract features from Lamb wave signals that can be linked with damage for subsequent localization and quantification…”
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