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

DOI: 10.3390/s23052572
Published: 2023 Feb 25
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s23052572,
  title = {Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges.},
  author = {Kao SP and Chang YC and Wang FL},
  year = {2023},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s23052572},
  url = {https://doi.org/10.3390/s23052572}
}

RIS

TY  - JOUR
TI  - Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges.
AU  - Kao SP
AU  - Chang YC
AU  - Wang FL
PY  - 2023
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s23052572
UR  - https://doi.org/10.3390/s23052572
ER  -

APA

SP, K., YC, C., & FL, W. (2023). Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s23052572

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pubmed · retrieved 2026-11-10T07:53:06.451Z