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Artigo de periodico
Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures (2025)
Dias, Fabio Felix ; Ponti, Moacir Antonelli ; Minghim, Rosane
Source: Ecological Informatics. Unidade: ICMC
Subjects: REDES NEURAIS, 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. Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures. Ecological Informatics, v. 90, p. 1-12, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.ecoinf.2025.103232. Acesso em: 08 out. 2025.
APA
Dias, F. F., Ponti, M. A., & Minghim, R. (2025). Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures. Ecological Informatics, 90, 1-12. doi:10.1016/j.ecoinf.2025.103232
NLM
Dias FF, Ponti MA, Minghim R. Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures [Internet]. Ecological Informatics. 2025 ; 90 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.ecoinf.2025.103232
Vancouver
Dias FF, Ponti MA, Minghim R. Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures [Internet]. Ecological Informatics. 2025 ; 90 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.ecoinf.2025.103232
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: 08 out. 2025.
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 2025 out. 08 ] 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 2025 out. 08 ] Available from: https://doi.org/10.1007/s00521-021-06501-w
Artigo de periodico
Visual active learning for labeling: a case for soundscape ecology data (2021)
Huancapaza, Liz ; Ribeiro, Milton Cezar ; Minghim, Rosane
Source: Information. Unidade: ICMC
Subjects: VISUALIZAÇÃO, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, SOM, MONITORAMENTO BIOLÓGICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HUANCAPAZA, Liz e RIBEIRO, Milton Cezar e MINGHIM, Rosane. Visual active learning for labeling: a case for soundscape ecology data. Information, v. 12, n. 7, p. 1-17, 2021Tradução . . Disponível em: https://doi.org/10.3390/info12070265. Acesso em: 08 out. 2025.
APA
Huancapaza, L., Ribeiro, M. C., & Minghim, R. (2021). Visual active learning for labeling: a case for soundscape ecology data. Information, 12( 7), 1-17. doi:10.3390/info12070265
NLM
Huancapaza L, Ribeiro MC, Minghim R. Visual active learning for labeling: a case for soundscape ecology data [Internet]. Information. 2021 ; 12( 7): 1-17.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/info12070265
Vancouver
Huancapaza L, Ribeiro MC, Minghim R. Visual active learning for labeling: a case for soundscape ecology data [Internet]. Information. 2021 ; 12( 7): 1-17.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/info12070265
Artigo de periodico
An adaptive boundary algorithm for the reconstruction of boundary and initial data using the method of fundamental solutions for the inverse Cauchy-Stefan problem (2021)
Reddy, Gujji Murali Mohan ; Nanda, P; Vynnycky, Michael ; Cuminato, José Alberto
Source: Computational and Applied Mathematics. Unidade: ICMC
Subjects: PROBLEMAS INVERSOS, MÉTODOS NUMÉRICOS, ALGORITMOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
REDDY, Gujji Murali Mohan et al. An adaptive boundary algorithm for the reconstruction of boundary and initial data using the method of fundamental solutions for the inverse Cauchy-Stefan problem. Computational and Applied Mathematics, v. 40, p. 1-26, 2021Tradução . . Disponível em: https://doi.org/10.1007/s40314-021-01454-1. Acesso em: 08 out. 2025.
APA
Reddy, G. M. M., Nanda, P., Vynnycky, M., & Cuminato, J. A. (2021). An adaptive boundary algorithm for the reconstruction of boundary and initial data using the method of fundamental solutions for the inverse Cauchy-Stefan problem. Computational and Applied Mathematics, 40, 1-26. doi:10.1007/s40314-021-01454-1
NLM
Reddy GMM, Nanda P, Vynnycky M, Cuminato JA. An adaptive boundary algorithm for the reconstruction of boundary and initial data using the method of fundamental solutions for the inverse Cauchy-Stefan problem [Internet]. Computational and Applied Mathematics. 2021 ; 40 1-26.[citado 2025 out. 08 ] Available from: https://doi.org/10.1007/s40314-021-01454-1
Vancouver
Reddy GMM, Nanda P, Vynnycky M, Cuminato JA. An adaptive boundary algorithm for the reconstruction of boundary and initial data using the method of fundamental solutions for the inverse Cauchy-Stefan problem [Internet]. Computational and Applied Mathematics. 2021 ; 40 1-26.[citado 2025 out. 08 ] Available from: https://doi.org/10.1007/s40314-021-01454-1
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: 08 out. 2025.
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 2025 out. 08 ] 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 2025 out. 08 ] Available from: https://doi.org/10.3390/a14120344

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