PGCNet: a Transformer-CNN hybrid segmentation model for pine wilt disease identification.

Liu J, Zhang Y, Chen X

DOI: 10.3389/fpls.2026.1760648
Published: 2026
Container: Frontiers in plant science
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fpls.2026.1760648,
  title = {PGCNet: a Transformer-CNN hybrid segmentation model for pine wilt disease identification.},
  author = {Liu J and Zhang Y and Chen X},
  year = {2026},
  journal = {Frontiers in plant science},
  doi = {10.3389/fpls.2026.1760648},
  url = {https://doi.org/10.3389/fpls.2026.1760648}
}

RIS

TY  - JOUR
TI  - PGCNet: a Transformer-CNN hybrid segmentation model for pine wilt disease identification.
AU  - Liu J
AU  - Zhang Y
AU  - Chen X
PY  - 2026
JO  - Frontiers in plant science
DO  - 10.3389/fpls.2026.1760648
UR  - https://doi.org/10.3389/fpls.2026.1760648
ER  -

APA

J, L., Y, Z., & X, C. (2026). PGCNet: a Transformer-CNN hybrid segmentation model for pine wilt disease identification.. Frontiers in plant science. https://doi.org/10.3389/fpls.2026.1760648

Source records

pubmed · retrieved 2026-09-25T15:39:53.260Z