ReP USP - Resultado da busca

Filtros : "Irlanda" "PONTI, MOACIR ANTONELLI" Removidos: "Ferriani, Rui Alberto" "ALMEIDA, MARIANA BORTHOLAZZI" Limpar

Filtros

Artigo de periodico
A classification and quantification approach to generate features in soundscape ecology using neural networks (2022)
Dias, Fabio Felix ; Ponti, Moacir Antonelli ; Minghim, Rosane
Source: Neural Computing and Applications. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ACÚSTICA, MONITORAMENTO AMBIENTAL, PÁSSAROS, ANURA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DIAS, Fabio Felix e PONTI, Moacir Antonelli e MINGHIM, Rosane. A classification and quantification approach to generate features in soundscape ecology using neural networks. Neural Computing and Applications, v. 34, n. 3, p. 1923-1937, 2022Tradução . . Disponível em: https://doi.org/10.1007/s00521-021-06501-w. Acesso em: 07 ago. 2024.
APA
Dias, F. F., Ponti, M. A., & Minghim, R. (2022). A classification and quantification approach to generate features in soundscape ecology using neural networks. Neural Computing and Applications, 34( 3), 1923-1937. doi:10.1007/s00521-021-06501-w
NLM
Dias FF, Ponti MA, Minghim R. A classification and quantification approach to generate features in soundscape ecology using neural networks [Internet]. Neural Computing and Applications. 2022 ; 34( 3): 1923-1937.[citado 2024 ago. 07 ] Available from: https://doi.org/10.1007/s00521-021-06501-w
Vancouver
Dias FF, Ponti MA, Minghim R. A classification and quantification approach to generate features in soundscape ecology using neural networks [Internet]. Neural Computing and Applications. 2022 ; 34( 3): 1923-1937.[citado 2024 ago. 07 ] Available from: https://doi.org/10.1007/s00521-021-06501-w
Artigo de periodico
A visual mining approach to improved multiple-instance learning (2021)
Castelo, Sonia; Ponti, Moacir Antonelli ; Minghim, Rosane
Source: Algorithms. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, VISUALIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASTELO, Sonia e PONTI, Moacir Antonelli e MINGHIM, Rosane. A visual mining approach to improved multiple-instance learning. Algorithms, v. 14, n. 12, p. 1-28, 2021Tradução . . Disponível em: https://doi.org/10.3390/a14120344. Acesso em: 07 ago. 2024.
APA
Castelo, S., Ponti, M. A., & Minghim, R. (2021). A visual mining approach to improved multiple-instance learning. Algorithms, 14( 12), 1-28. doi:10.3390/a14120344
NLM
Castelo S, Ponti MA, Minghim R. A visual mining approach to improved multiple-instance learning [Internet]. Algorithms. 2021 ; 14( 12): 1-28.[citado 2024 ago. 07 ] Available from: https://doi.org/10.3390/a14120344
Vancouver
Castelo S, Ponti MA, Minghim R. A visual mining approach to improved multiple-instance learning [Internet]. Algorithms. 2021 ; 14( 12): 1-28.[citado 2024 ago. 07 ] Available from: https://doi.org/10.3390/a14120344

Digital Library of Intellectual Production of Universidade de São Paulo 2012 - 2024