skip to main content
Idioma:

Unlabeled AnuraSet: A dataset for leveraging unlabeled data in machine learning models for passive acoustic monitoring

Cañas, Juan Sebastián ; María Paula, Toro-Gómez ; Larissa Sayuri, Moreira Sugai ; Toledo, Luis Felipe ; Franco Leandro, De Souza ; Selvino, Neckel De Oliveira ; Rogerio, Pereira Bastos ; Diego, Llusia ; Juan Sebastián, Ulloa

Zenodo 2024

Texto completo disponível

Citações Citado por
  • Título:
    Unlabeled AnuraSet: A dataset for leveraging unlabeled data in machine learning models for passive acoustic monitoring
  • Autor: Cañas, Juan Sebastián ; María Paula, Toro-Gómez ; Larissa Sayuri, Moreira Sugai ; Toledo, Luis Felipe ; Franco Leandro, De Souza ; Selvino, Neckel De Oliveira ; Rogerio, Pereira Bastos ; Diego, Llusia ; Juan Sebastián, Ulloa
  • Assuntos: Bioacoustics ; neotropical anuran ; passive acoustic monitoring ; self-supervised learning ; soundscape ; unlabeled
  • Notas: RelationTypeNote: IsVariantFormOf -- 10.5281/zenodo.8342596
    10.1038/s41597-023-02666-2
    10.5281/zenodo.8342596
    RelationTypeNote: Documents -- 10.1038/s41597-023-02666-2
    RelationTypeNote: HasVersion -- 10.5281/zenodo.11244814
    2052-4463
    10.5281/zenodo.11244814
  • Descrição: The Unlabeled AnuraSet (U-AnuraSet) is an extension of the original AnuraSet dataset. It consists of soundscape recordings from passive acoustic monitoring conducted in Brazil. The recording sites are identical to those in the original AnuraSet. Each site comprises 2,666 one-minute raw audio files of unlabeled data. The U-AnuraSet is publicly available to encourage machine learning researchers to explore innovative methods for leveraging unlabeled data in the training of models aimed at solving problems such as anuran call identification. If you find the Unlabeled AnuraSet useful for your research, please consider citing it as follows: Cañas, J.S., Toro-Gómez, M.P., Sugai, L.S.M., et al. A dataset for benchmarking Neotropical anuran calls identification in passive acoustic monitoring. Sci Data 10, 771 (2023). https://doi.org/10.1038/s41597-023-02666-2
  • Editor: Zenodo
  • Data de criação/publicação: 2024
  • Idioma: Inglês
Voltar para lista de resultados

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

Buscando em bases de dados remotas. Favor aguardar.