These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

154 related articles for article (PubMed ID: 34502724)

  • 1. Deep-Compact-Clustering Based Anomaly Detection Applied to Electromechanical Industrial Systems.
    Arellano-Espitia F; Delgado-Prieto M; Gonzalez-Abreu AD; Saucedo-Dorantes JJ; Osornio-Rios RA
    Sensors (Basel); 2021 Aug; 21(17):. PubMed ID: 34502724
    [TBL] [Abstract][Full Text] [Related]  

  • 2. OutlierNets: Highly Compact Deep Autoencoder Network Architectures for On-Device Acoustic Anomaly Detection.
    Abbasi S; Famouri M; Shafiee MJ; Wong A
    Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300545
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep Convolutional Clustering-Based Time Series Anomaly Detection.
    Chadha GS; Islam I; Schwung A; Ding SX
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450930
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DOC-IDS: A Deep Learning-Based Method for Feature Extraction and Anomaly Detection in Network Traffic.
    Yoshimura N; Kuzuno H; Shiraishi Y; Morii M
    Sensors (Basel); 2022 Jun; 22(12):. PubMed ID: 35746191
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multilayer one-class extreme learning machine.
    Dai H; Cao J; Wang T; Deng M; Yang Z
    Neural Netw; 2019 Jul; 115():11-22. PubMed ID: 30921561
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Smart-Anomaly-Detection System for Industrial Machines Based on Feature Autoencoder and Deep Learning.
    Ahmed I; Ahmad M; Chehri A; Jeon G
    Micromachines (Basel); 2023 Jan; 14(1):. PubMed ID: 36677215
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Wind turbine anomaly detection based on SCADA: A deep autoencoder enhanced by fault instances.
    Liu J; Yang G; Li X; Wang Q; He Y; Yang X
    ISA Trans; 2023 Aug; 139():586-605. PubMed ID: 37076374
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability.
    Xie W; Li Z; Xu Y; Gardoni P; Li W
    Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35591006
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Fault Detection and Diagnosis Using Combined Autoencoder and Long Short-Term Memory Network.
    Park P; Marco PD; Shin H; Bang J
    Sensors (Basel); 2019 Oct; 19(21):. PubMed ID: 31652821
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network.
    Gan Y; Huang X; Zou G; Zhou S; Guan J
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35172334
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Anomaly detection in radiotherapy plans using deep autoencoder networks.
    Huang P; Shang J; Xu Y; Hu Z; Zhang K; Dai J; Yan H
    Front Oncol; 2023; 13():1142947. PubMed ID: 36998450
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Diagnosis Methodology Based on Deep Feature Learning for Fault Identification in Metallic, Hybrid and Ceramic Bearings.
    Saucedo-Dorantes JJ; Arellano-Espitia F; Delgado-Prieto M; Osornio-Rios RA
    Sensors (Basel); 2021 Aug; 21(17):. PubMed ID: 34502720
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multi-mode non-Gaussian variational autoencoder network with missing sources for anomaly detection of complex electromechanical equipment.
    Luo Q; Chen J; Zi Y; Chang Y; Feng Y
    ISA Trans; 2023 Mar; 134():144-158. PubMed ID: 36150902
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Novel Deep Learning Method for Intelligent Fault Diagnosis of Rotating Machinery Based on Improved CNN-SVM and Multichannel Data Fusion.
    Gong W; Chen H; Zhang Z; Zhang M; Wang R; Guan C; Wang Q
    Sensors (Basel); 2019 Apr; 19(7):. PubMed ID: 30970672
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Novel Deep Learning Model for the Detection and Identification of Rolling Element-Bearing Faults.
    Shenfield A; Howarth M
    Sensors (Basel); 2020 Sep; 20(18):. PubMed ID: 32911771
    [TBL] [Abstract][Full Text] [Related]  

  • 16. GRU-Based Denoising Autoencoder for Detection and Clustering of Unknown Single and Concurrent Faults during System Integration Testing of Automotive Software Systems.
    Abboush M; Knieke C; Rausch A
    Sensors (Basel); 2023 Jul; 23(14):. PubMed ID: 37514900
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep-Learning-Based Methodology for Fault Diagnosis in Electromechanical Systems.
    Arellano-Espitia F; Delgado-Prieto M; Martinez-Viol V; Saucedo-Dorantes JJ; Osornio-Rios RA
    Sensors (Basel); 2020 Jul; 20(14):. PubMed ID: 32708574
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The Robust Multi-Scale Deep-SVDD Model for Anomaly Online Detection of Rolling Bearings.
    Kou L; Chen J; Qin Y; Mao W
    Sensors (Basel); 2022 Jul; 22(15):. PubMed ID: 35957238
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Anomaly Detection for Sensor Signals Utilizing Deep Learning Autoencoder-Based Neural Networks.
    Esmaeili F; Cassie E; Nguyen HPT; Plank NOV; Unsworth CP; Wang A
    Bioengineering (Basel); 2023 Mar; 10(4):. PubMed ID: 37106591
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine fault detection methods based on machine learning algorithms: A review.
    Ciaburro G
    Math Biosci Eng; 2022 Aug; 19(11):11453-11490. PubMed ID: 36124599
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.