Partially supervised anomaly detection using convex hulls on a 2D parameter space (2013)
- Authors:
- Autor USP: PONTI JUNIOR, MOACIR PEREIRA - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-642-40705-5_1
- Subjects: COMPUTAÇÃO GRÁFICA; PROCESSAMENTO DE IMAGENS; INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: Springer-Verlag
- Publisher place: Berlin
- Date published: 2013
- Source:
- Título do periódico: Lecture Notes in Artificial Intelligence
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 8183, p. 1-8, 2013
- Conference titles: IAPR International Workshop on Partially Supervised Learning - PSL
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
COSTA, Gabriel B. P e PONTI JUNIOR, Moacir Pereira e FRERY ORGAMBIDE, Alejandro C. Partially supervised anomaly detection using convex hulls on a 2D parameter space. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. Disponível em: https://doi.org/10.1007/978-3-642-40705-5_1. Acesso em: 19 abr. 2024. , 2013 -
APA
Costa, G. B. P., Ponti Junior, M. P., & Frery Orgambide, A. C. (2013). Partially supervised anomaly detection using convex hulls on a 2D parameter space. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. doi:10.1007/978-3-642-40705-5_1 -
NLM
Costa GBP, Ponti Junior MP, Frery Orgambide AC. Partially supervised anomaly detection using convex hulls on a 2D parameter space [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8183 1-8.[citado 2024 abr. 19 ] Available from: https://doi.org/10.1007/978-3-642-40705-5_1 -
Vancouver
Costa GBP, Ponti Junior MP, Frery Orgambide AC. Partially supervised anomaly detection using convex hulls on a 2D parameter space [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8183 1-8.[citado 2024 abr. 19 ] Available from: https://doi.org/10.1007/978-3-642-40705-5_1 - Does background intensity estimation influence the iterative restoration of microscope images?
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Informações sobre o DOI: 10.1007/978-3-642-40705-5_1 (Fonte: oaDOI API)
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