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 *

143 related articles for article (PubMed ID: 38543988)

  • 1. Crack Detection and Analysis of Concrete Structures Based on Neural Network and Clustering.
    Choi Y; Park HW; Mi Y; Song S
    Sensors (Basel); 2024 Mar; 24(6):. PubMed ID: 38543988
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Concrete Surface Crack Recognition Based on Coordinate Attention Neural Networks.
    Zhang Y; Wang Z
    Comput Intell Neurosci; 2022; 2022():7454746. PubMed ID: 35990168
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Vision-Based Autonomous Crack Detection of Concrete Structures Using a Fully Convolutional Encoder-Decoder Network.
    Islam MMM; Kim JM
    Sensors (Basel); 2019 Sep; 19(19):. PubMed ID: 31574963
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Learning to Detect Cracks on Damaged Concrete Surfaces Using Two-Branched Convolutional Neural Network.
    Lee J; Kim HS; Kim N; Ryu EM; Kang JW
    Sensors (Basel); 2019 Nov; 19(21):. PubMed ID: 31689987
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Assessment of Convolutional Neural Network Pre-Trained Models for Detection and Orientation of Cracks.
    Qayyum W; Ehtisham R; Bahrami A; Camp C; Mir J; Ahmad A
    Materials (Basel); 2023 Jan; 16(2):. PubMed ID: 36676563
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Application of Crack Identification Techniques for an Aging Concrete Bridge Inspection Using an Unmanned Aerial Vehicle.
    Kim IH; Jeon H; Baek SC; Hong WH; Jung HJ
    Sensors (Basel); 2018 Jun; 18(6):. PubMed ID: 29890652
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Enhanced Intelligent Identification of Concrete Cracks Using Multi-Layered Image Preprocessing-Aided Convolutional Neural Networks.
    Fu R; Xu H; Wang Z; Shen L; Cao M; Liu T; Novák D
    Sensors (Basel); 2020 Apr; 20(7):. PubMed ID: 32260302
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Vision and Deep Learning-Based Algorithms to Detect and Quantify Cracks on Concrete Surfaces from UAV Videos.
    Bhowmick S; Nagarajaiah S; Veeraraghavan A
    Sensors (Basel); 2020 Nov; 20(21):. PubMed ID: 33167411
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Mobile-DenseNet: Detection of building concrete surface cracks using a new fusion technique based on deep learning.
    Akgül İ
    Heliyon; 2023 Oct; 9(10):e21097. PubMed ID: 37886768
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An improved transformer-based concrete crack classification method.
    Ye G; Dai W; Tao J; Qu J; Zhu L; Jin Q
    Sci Rep; 2024 Mar; 14(1):6226. PubMed ID: 38485707
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An Ensemble Approach for Robust Automated Crack Detection and Segmentation in Concrete Structures.
    Sohaib M; Jamil S; Kim JM
    Sensors (Basel); 2024 Jan; 24(1):. PubMed ID: 38203119
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Mosaic crack mapping of footings by convolutional neural networks.
    Buatik A; Thansirichaisree P; Kalpiyapun P; Khademi N; Pasityothin I; Poovarodom N
    Sci Rep; 2024 Apr; 14(1):7851. PubMed ID: 38570570
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges.
    Kao SP; Chang YC; Wang FL
    Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904775
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An Automated Image-Based Multivariant Concrete Defect Recognition Using a Convolutional Neural Network with an Integrated Pooling Module.
    Kim B; Choi SW; Hu G; Lee DE; Serfa Juan RO
    Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590810
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic Detection of Cracks on Concrete Surfaces in the Presence of Shadows.
    Palevičius P; Pal M; Landauskas M; Orinaitė U; Timofejeva I; Ragulskis M
    Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632070
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automatic Concrete Damage Recognition Using Multi-Level Attention Convolutional Neural Network.
    Shin HK; Ahn YH; Lee SH; Kim HY
    Materials (Basel); 2020 Dec; 13(23):. PubMed ID: 33291411
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 2D Digital Image Correlation and Region-Based Convolutional Neural Network in Monitoring and Evaluation of Surface Cracks in Concrete Structural Elements.
    Słoński M; Tekieli M
    Materials (Basel); 2020 Aug; 13(16):. PubMed ID: 32785087
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique.
    Kim B; Cho S
    Sensors (Basel); 2018 Oct; 18(10):. PubMed ID: 30322206
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Improving the Concrete Crack Detection Process via a Hybrid Visual Transformer Algorithm.
    Shahin M; Chen FF; Maghanaki M; Hosseinzadeh A; Zand N; Khodadadi Koodiani H
    Sensors (Basel); 2024 May; 24(10):. PubMed ID: 38794102
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Multi-Stage Feature Aggregation and Structure Awareness Network for Concrete Bridge Crack Detection.
    Zhang E; Jiang T; Duan J
    Sensors (Basel); 2024 Feb; 24(5):. PubMed ID: 38475078
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.