On a Hybrid CNN-Driven Pipeline for 3D Defect Localisation in the Inspection of EV Battery Modules

Paolo Catti, Luca Fabbro, Nikolaos Nikolakis

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DOI: 10.3390/s25247613
Published: 2025-12-15
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s25247613,
  title = {On a Hybrid CNN-Driven Pipeline for 3D Defect Localisation in the Inspection of EV Battery Modules},
  author = {Paolo Catti and Luca Fabbro and Nikolaos Nikolakis},
  year = {2025},
  journal = {Sensors},
  doi = {10.3390/s25247613},
  url = {https://doi.org/10.3390/s25247613}
}

RIS

TY  - JOUR
TI  - On a Hybrid CNN-Driven Pipeline for 3D Defect Localisation in the Inspection of EV Battery Modules
AU  - Paolo Catti
AU  - Luca Fabbro
AU  - Nikolaos Nikolakis
PY  - 2025
JO  - Sensors
DO  - 10.3390/s25247613
UR  - https://doi.org/10.3390/s25247613
ER  -

APA

Catti, P., Fabbro, L., & Nikolakis, N. (2025). On a Hybrid CNN-Driven Pipeline for 3D Defect Localisation in the Inspection of EV Battery Modules. Sensors. https://doi.org/10.3390/s25247613

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crossref · retrieved 2026-09-26T11:27:05.090Z