IRIS

Cesarini, V., Robotti, C., Piromalli, Y., Mozzanica, F., Schindler, A., Saggio, G., et al. (2022). Machine Learning-based Study of Dysphonic Voices for the Identification and Differentiation of Vocal Cord Paralysis and Vocal Nodules. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) (pp.265-272). SCITEPRESS [10.5220/0010913800003123].

Machine Learning-based Study of Dysphonic Voices for the Identification and Differentiation of Vocal Cord Paralysis and Vocal Nodules

Cesarini V.;Saggio G.;Costantini G.
2022-01-01
BIOSIGNALS 2022 - International Conference on Bio-Inspired Systems and Signal Processing
Rilevanza internazionale
contributo
2022
Settore ING-IND/31 - ELETTROTECNICA
English
Intervento a convegno
Cesarini, V., Robotti, C., Piromalli, Y., Mozzanica, F., Schindler, A., Saggio, G., et al. (2022). Machine Learning-based Study of Dysphonic Voices for the Identification and Differentiation of Vocal Cord Paralysis and Vocal Nodules. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) (pp.265-272). SCITEPRESS [10.5220/0010913800003123].
Cesarini, V; Robotti, C; Piromalli, Y; Mozzanica, F; Schindler, A; Saggio, G; Costantini, G
02 - Intervento a convegno
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/331227
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 1
social impact