A machine learning based method for staff removal (2014)
- Authors:
- USP affiliated authors: HIRATA JUNIOR, ROBERTO - IME ; HIRATA, NINA SUMIKO TOMITA - IME
- Unidade: IME
- DOI: 10.1109/ICPR.2014.545
- Subjects: INTELIGÊNCIA ARTIFICIAL; APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE CARACTERES ACÚSTICOS; COMPUTAÇÃO MUSICAL
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2014
- Source:
- Título: Proceedings
- Conference titles: International Conference on Pattern Recognition - ICPR
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MONTAGNER, Igor dos Santos e HIRATA JÚNIOR, Roberto e HIRATA, Nina Sumiko Tomita. A machine learning based method for staff removal. 2014, Anais.. Los Alamitos: IEEE, 2014. Disponível em: https://doi.org/10.1109/ICPR.2014.545. Acesso em: 28 dez. 2025. -
APA
Montagner, I. dos S., Hirata Júnior, R., & Hirata, N. S. T. (2014). A machine learning based method for staff removal. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICPR.2014.545 -
NLM
Montagner I dos S, Hirata Júnior R, Hirata NST. A machine learning based method for staff removal [Internet]. Proceedings. 2014 ;[citado 2025 dez. 28 ] Available from: https://doi.org/10.1109/ICPR.2014.545 -
Vancouver
Montagner I dos S, Hirata Júnior R, Hirata NST. A machine learning based method for staff removal [Internet]. Proceedings. 2014 ;[citado 2025 dez. 28 ] Available from: https://doi.org/10.1109/ICPR.2014.545 - Comics image processing: learning to segment text
- Kernel approximations for W-operator learning
- Staff removal using image operator learning
- Two-stage binary image operator design: an approach based on interaction information
- An information theory framework for two-stage binary image operator design
- Learning to remove staff lines from music score images
- NILC: a two level learning algorithm with operator selection
- Image operator learning and applications
- Image operator learning based on local features
- Basis computation algorithms
Informações sobre o DOI: 10.1109/ICPR.2014.545 (Fonte: oaDOI API)
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