Acoustic classification of false killer whales in the Hawaiian islands based on comprehensive vocal repertoire.
JASA Express Lett
; 1(7): 071201, 2021 07.
Article
en En
| MEDLINE
| ID: mdl-36154647
ABSTRACT
Use of underwater passive acoustic datasets for species-specific inference requires robust classification systems to identify encounters to species from characteristics of detected sounds. A suite of routines designed to efficiently detect cetacean sounds, extract features, and classify the detection to species is described using ship-based, visually verified detections of false killer whales (Pseudorca crassidens). The best-performing model included features from clicks, whistles, and burst pulses, which correctly classified 99.6% of events. This case study illustrates use of these tools to build classifiers for any group of cetacean species and assess classification confidence when visual confirmation is not available.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Delfines
Tipo de estudio:
Prognostic_studies
Límite:
Animals
País/Región como asunto:
America do norte
Idioma:
En
Revista:
JASA Express Lett
Año:
2021
Tipo del documento:
Article
País de afiliación:
Estados Unidos