Defect-Mask2Former: An Improved Semantic Segmentation Model for Precise Small-Sized Defect Detection on Large-Sized Timbers

Mingming Qin, Hongxu Li, Yuxiang Huang, Xingyu Tong, Zhihong Liang

Open source

DOI: 10.3390/s26072254
Published: 2026-04-06
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s26072254,
  title = {Defect-Mask2Former: An Improved Semantic Segmentation Model for Precise Small-Sized Defect Detection on Large-Sized Timbers},
  author = {Mingming Qin and Hongxu Li and Yuxiang Huang and Xingyu Tong and Zhihong Liang},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26072254},
  url = {https://doi.org/10.3390/s26072254}
}

RIS

TY  - JOUR
TI  - Defect-Mask2Former: An Improved Semantic Segmentation Model for Precise Small-Sized Defect Detection on Large-Sized Timbers
AU  - Mingming Qin
AU  - Hongxu Li
AU  - Yuxiang Huang
AU  - Xingyu Tong
AU  - Zhihong Liang
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26072254
UR  - https://doi.org/10.3390/s26072254
ER  -

APA

Qin, M., Li, H., Huang, Y., Tong, X., & Liang, Z. (2026). Defect-Mask2Former: An Improved Semantic Segmentation Model for Precise Small-Sized Defect Detection on Large-Sized Timbers. Sensors. https://doi.org/10.3390/s26072254

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crossref · retrieved 2026-11-10T06:56:20.767Z