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A fabric defect detection model based on improved Swin Transformer with large kernel attention

Chengming Liu et al.

Journal of the Textile Institute2026https://doi.org/10.1080/00405000.2025.2606612article
AJG 1
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0.50

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https://doi.org/https://doi.org/10.1080/00405000.2025.2606612

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@article{chengming2026,
  title        = {{A fabric defect detection model based on improved Swin Transformer with large kernel attention}},
  author       = {Chengming Liu et al.},
  journal      = {Journal of the Textile Institute},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/00405000.2025.2606612},
}

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A fabric defect detection model based on improved Swin Transformer with large kernel attention

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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