• Media type: E-Article
  • Title: Trainable Filters for the Identification of Anomalies in Cosmogenic Isotope Data
  • Contributor: Neocleous, Andreas; Azzopardi, George; Kuitems, Margot; Scifo, Andrea; Dee, Michael
  • Published: Institute of Electrical and Electronics Engineers (IEEE), 2019
  • Published in: IEEE Access, 7 (2019), Seite 24585-24592
  • Language: Not determined
  • DOI: 10.1109/access.2019.2900123
  • ISSN: 2169-3536
  • Keywords: General Engineering ; General Materials Science ; General Computer Science
  • Origination:
  • Footnote:
  • Access State: Open Access