A Semi-Automatic Labeling Framework for PCB Defects via Deep Embeddings and Density-Aware Clustering.

Lee SJ, Seo SB, Bae YS.

Open source

DOI: 10.3390/s25206470
Published: 2025-10-19
Container: Sensors (Basel)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s25206470,
  title = {A Semi-Automatic Labeling Framework for PCB Defects via Deep Embeddings and Density-Aware Clustering.},
  author = {Lee SJ and  Seo SB and  Bae YS.},
  year = {2025},
  journal = {Sensors (Basel)},
  doi = {10.3390/s25206470},
  url = {https://doi.org/10.3390/s25206470}
}

RIS

TY  - JOUR
TI  - A Semi-Automatic Labeling Framework for PCB Defects via Deep Embeddings and Density-Aware Clustering.
AU  - Lee SJ
AU  -  Seo SB
AU  -  Bae YS.
PY  - 2025
JO  - Sensors (Basel)
DO  - 10.3390/s25206470
UR  - https://doi.org/10.3390/s25206470
ER  -

APA

SJ, L., SB, S., & YS., B. (2025). A Semi-Automatic Labeling Framework for PCB Defects via Deep Embeddings and Density-Aware Clustering.. Sensors (Basel). https://doi.org/10.3390/s25206470

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europe-pmc · retrieved 2026-09-26T15:08:26.617Z
doaj · retrieved 2026-09-26T15:08:26.613Z