TraiRANN: evaluating data reduction methods for neural network training in medical applications (2025)
- Authors:
- USP affiliated authors: TRAINA JUNIOR, CAETANO - ICMC ; TRAINA, AGMA JUCI MACHADO - ICMC ; UCHIDA, MARIANA AYA SUZUKI - ICMC ; ELEUTERIO, IGOR ALBERTE RODRIGUES - ICMC ; COSTA, MARCUS VINICIUS LOBO - ICMC ; ARBOLEDA, RODRIGO CÉSAR - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-031-94934-0_51
- Subjects: REDES NEURAIS; DIAGNÓSTICO POR IMAGEM; RECONHECIMENTO DE IMAGEM; TECNOLOGIAS DA SAÚDE; COVID-19; LEUCEMIA
- Keywords: Training data selection; Relative Neighborhood Graph; RNG; Convolutional Neural Network - CNN; Classification; Medical Imagings
- Agências de fomento:
- Language: Inglês
- Objetivos de Desenvolvimento Sustentável (ODS):
03. Saúde e bem-estar
- Imprenta:
- Source:
- Título: IFMBE Proceedings
- ISSN: 1680-0737
- Volume/Número/Paginação/Ano: v. 127, p. 492-501, 2025
- Conference titles: Brazilian Congress on Biomedical Engineering - CBEB
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
UCHIDA, Mariana Aya Suzuki et al. TraiRANN: evaluating data reduction methods for neural network training in medical applications. IFMBE Proceedings. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-94934-0_51. Acesso em: 13 fev. 2026. , 2025 -
APA
Uchida, M. A. S., Eleutério, I. A. R., Costa, M. V. L., Arboleda, R. C., Traina Junior, C., & Traina, A. J. M. (2025). TraiRANN: evaluating data reduction methods for neural network training in medical applications. IFMBE Proceedings. Cham: Springer. doi:10.1007/978-3-031-94934-0_51 -
NLM
Uchida MAS, Eleutério IAR, Costa MVL, Arboleda RC, Traina Junior C, Traina AJM. TraiRANN: evaluating data reduction methods for neural network training in medical applications [Internet]. IFMBE Proceedings. 2025 ; 127 492-501.[citado 2026 fev. 13 ] Available from: https://doi.org/10.1007/978-3-031-94934-0_51 -
Vancouver
Uchida MAS, Eleutério IAR, Costa MVL, Arboleda RC, Traina Junior C, Traina AJM. TraiRANN: evaluating data reduction methods for neural network training in medical applications [Internet]. IFMBE Proceedings. 2025 ; 127 492-501.[citado 2026 fev. 13 ] Available from: https://doi.org/10.1007/978-3-031-94934-0_51 - Efficient reuse of metric indexes for multi-resolution queries
- Data augmentation for medical image segmentation: a comparative analysis of traditional techniques and synthetic data generation
- Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings
- DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images
- KluSIM: speeding up k-medoids clustering over dimensional data with metric access method
- Similarity-slim extension: reducing financial and computational costs of similarity queries in document collections in NoSQL databases
- MIGUE-Sim: speeding up similarity queries with native RDBMS resources
- A novel approach to reduce the financial and computational costs of similarity queries over document collections in NoSQL databases
- Upgraded SemIndex prototype supporting intelligent database keyword queries through disambiguation, query as you type, and parallel search algorithms
- Content-based image retrieval using approximate shape of objects
Informações sobre o DOI: 10.1007/978-3-031-94934-0_51 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 3273847.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
