Source: LNCS - Lecture Notes in Computer Science. Conference titles: International Conference. Unidades: FEARP, FMRP
Subjects: LINGUAGEM, DIREITO, TERMINOLOGIA JURÍDICA, SEMÂNTICA, REDE NERVOSA
ABNT
RAZEIRA, Rafael Mecheseregian e RODELLO, Ildeberto Aparecido. A LSTM recurrent neural network implementation for classifying entities on brazilian legal documents. LNCS - Lecture Notes in Computer Science. Heidelberg: Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto, Universidade de São Paulo. Disponível em: http://dx.doi.org/10.1007/978-3-030-86960-1_48. Acesso em: 18 mar. 2025. , 2021APA
Razeira, R. M., & Rodello, I. A. (2021). A LSTM recurrent neural network implementation for classifying entities on brazilian legal documents. LNCS - Lecture Notes in Computer Science. Heidelberg: Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto, Universidade de São Paulo. doi:10.1007/978-3-030-86960-1_48NLM
Razeira RM, Rodello IA. A LSTM recurrent neural network implementation for classifying entities on brazilian legal documents [Internet]. LNCS - Lecture Notes in Computer Science. 2021 ;( 12950): 648–656.[citado 2025 mar. 18 ] Available from: http://dx.doi.org/10.1007/978-3-030-86960-1_48Vancouver
Razeira RM, Rodello IA. A LSTM recurrent neural network implementation for classifying entities on brazilian legal documents [Internet]. LNCS - Lecture Notes in Computer Science. 2021 ;( 12950): 648–656.[citado 2025 mar. 18 ] Available from: http://dx.doi.org/10.1007/978-3-030-86960-1_48