Cargando…
Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning
Automatic species classification of birds from their sound is a computational tool of increasing importance in ecology, conservation monitoring and vocal communication studies. To make classification useful in practice, it is crucial to improve its accuracy while ensuring that it can run at big data...
Autores principales: | Stowell, Dan, Plumbley, Mark D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106198/ https://www.ncbi.nlm.nih.gov/pubmed/25083350 http://dx.doi.org/10.7717/peerj.488 |
Ejemplares similares
-
Strong host phylogenetic and ecological effects on host competency for avian influenza in Australian wild birds
por: Wille, Michelle, et al.
Publicado: (2023) -
Adaptive representations of sound for automatic insect recognition
por: Faiß, Marius, et al.
Publicado: (2023) -
Computational analysis of sound scenes and events
por: Virtanen, Tuomas, et al.
Publicado: (2017) -
A bird's-eye view on turbulence: seabird foraging associations with evolving surface flow features
por: Lieber, Lilian, et al.
Publicado: (2021) -
Stable producer–scrounger dynamics in wild birds: sociability and learning speed covary with scrounging behaviour
por: Aplin, L. M., et al.
Publicado: (2017)