Deep learning for automated analysis of fish abundance: the benefits of training across multiple habitats.

Ditria, Ellen M; Sievers, Michael; Lopez-Marcano, Sebastian; Jinks, Eric L; Connolly, Rod M

Ditria, Ellen M; Sievers, Michael; Lopez-Marcano, Sebastian; Jinks, Eric L; Connolly, Rod M.

Afiliação

Ditria EM; Australian Rivers Institute - Coast & Estuaries, and School of Environment and Science, Griffith University, Gold Coast, QLD, 4222, Australia. ellen.ditria@griffithuni.edu.au.
Sievers M; Australian Rivers Institute - Coast & Estuaries, and School of Environment and Science, Griffith University, Gold Coast, QLD, 4222, Australia.
Lopez-Marcano S; Australian Rivers Institute - Coast & Estuaries, and School of Environment and Science, Griffith University, Gold Coast, QLD, 4222, Australia.
Jinks EL; Australian Rivers Institute - Coast & Estuaries, and School of Environment and Science, Griffith University, Gold Coast, QLD, 4222, Australia.
Connolly RM; Australian Rivers Institute - Coast & Estuaries, and School of Environment and Science, Griffith University, Gold Coast, QLD, 4222, Australia.

Environ Monit Assess ; 192(11): 698, 2020 Oct 12.

Article em En | MEDLINE | ID: mdl-33044609

Assuntos

Aprendizado Profundo; Monitoramento Ambiental; Animais; Ecossistema; Meio Ambiente; Peixes; Humanos

Palavras-chave

Computer vision; Machine learning; MaxN; Monitoring; Reef; Seagrass

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Aprendizado Profundo Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo

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XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Aprendizado Profundo Idioma: En Ano de publicação: 2020 Tipo de documento: Article