Semantic Segmentation-Guided Reconstruction and Artistic Style Synthesis of Intangible Cultural Heritage Patterns Using a Deep Learning Framework.

Zhan Z, Luo G

DOI: 10.3791/71577
Published: 2026 Aug 14
Container: Journal of visualized experiments : JoVE
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3791/71577,
  title = {Semantic Segmentation-Guided Reconstruction and Artistic Style Synthesis of Intangible Cultural Heritage Patterns Using a Deep Learning Framework.},
  author = {Zhan Z and Luo G},
  year = {2026},
  journal = {Journal of visualized experiments : JoVE},
  doi = {10.3791/71577},
  url = {https://doi.org/10.3791/71577}
}

RIS

TY  - JOUR
TI  - Semantic Segmentation-Guided Reconstruction and Artistic Style Synthesis of Intangible Cultural Heritage Patterns Using a Deep Learning Framework.
AU  - Zhan Z
AU  - Luo G
PY  - 2026
JO  - Journal of visualized experiments : JoVE
DO  - 10.3791/71577
UR  - https://doi.org/10.3791/71577
ER  -

APA

Z, Z., & G, L. (2026). Semantic Segmentation-Guided Reconstruction and Artistic Style Synthesis of Intangible Cultural Heritage Patterns Using a Deep Learning Framework.. Journal of visualized experiments : JoVE. https://doi.org/10.3791/71577

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pubmed · retrieved 2026-09-25T02:47:17.118Z