High-Level Network-based Detection of Oral Cancer from ATR-FTIR Spectroscopy (2024)
- Authors:
- Autor USP: LIANG, ZHAO - FFCLRP
- Unidade: FFCLRP
- DOI: 10.1109/IJCNN60899.2024.10650557
- Subjects: NEOPLASIAS BUCAIS; REDES COMPLEXAS; SÉRIES DE FOURIER; BIOMARCADORES
- Keywords: High-Level Classification; Oral Cancer; ATRFTIR; Salivary Diagnosis; Complex Networks; Data Classification
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2024
- Source:
- Título: Proceedings
- Conference titles: International Joint Conference on Neural Networks (IJCNN)
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
LIMA FILHO, Ricardo B et al. High-Level Network-based Detection of Oral Cancer from ATR-FTIR Spectroscopy. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/IJCNN60899.2024.10650557. Acesso em: 02 jan. 2026. -
APA
Lima Filho, R. B., Fernandes, J. M., Ji, D., Liang, Z., Sabino-Silva, R., & Carneiro, M. G. (2024). High-Level Network-based Detection of Oral Cancer from ATR-FTIR Spectroscopy. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN60899.2024.10650557 -
NLM
Lima Filho RB, Fernandes JM, Ji D, Liang Z, Sabino-Silva R, Carneiro MG. High-Level Network-based Detection of Oral Cancer from ATR-FTIR Spectroscopy [Internet]. Proceedings. 2024 ;[citado 2026 jan. 02 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650557 -
Vancouver
Lima Filho RB, Fernandes JM, Ji D, Liang Z, Sabino-Silva R, Carneiro MG. High-Level Network-based Detection of Oral Cancer from ATR-FTIR Spectroscopy [Internet]. Proceedings. 2024 ;[citado 2026 jan. 02 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650557 - Redes de elementos complexos para processamento de informação
- Structural outlier detection: a tourist walk approach
- Network-based high level data classification
- Uncovering overlapping structures via stochastic competitive learning
- Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning
- Enhancing weak signal transmission through a feedforward network
- Multiple images set classification via network modularity
- Classification of multiple observation sets via network modularity
- Particle competition and cooperation in networks for semi-supervised learning with concept drift
- Aprendizado de máquina em redes complexas
Informações sobre o DOI: 10.1109/IJCNN60899.2024.10650557 (Fonte: oaDOI API)
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