Predictive models for the characterization of internal defects in additive materials from active thermography sequences supported by machine learning methods

  1. Rodríguez-Martín, M.
  2. Fueyo, J.G.
  3. Gonzalez-Aguilera, D.
  4. Madruga, F.J.
  5. García-Martín, R.
  6. Muñóz, Á.L.
  7. Pisonero, J.
Zeitschrift:
Sensors (Switzerland)

ISSN: 1424-8220

Datum der Publikation: 2020

Ausgabe: 20

Nummer: 14

Seiten: 1-26

Art: Artikel

DOI: 10.3390/S20143982 GOOGLE SCHOLAR lock_openOpen Access editor
Datenquelle: Scopus