Including conditional operators in content-based image retrieval in large sets of medical exams (2004)
- Authors:
- USP affiliated authors: TRAINA JUNIOR, CAETANO - ICMC ; TRAINA, AGMA JUCI MACHADO - ICMC
- School: ICMC
- Subject: COMPUTAÇÃO GRÁFICA
- Language: Inglês
- Imprenta:
- Publisher: IEEE Computer Society
- Place of publication: Los Alamitos
- Date published: 2004
- ISBN: 0769521045
- Source:
- Título do periódico: Proceedimgs
- Conference title: IEEE Symposium on Computer-Based Medical Systems
-
ABNT
TRAINA JUNIOR, Caetano e TRAINA, Agma Juci Machado e FIGUEIREDO, Josiel Maimoni de. Including conditional operators in content-based image retrieval in large sets of medical exams. 2004, Anais.. Los Alamitos: IEEE Computer Society, 2004. . Acesso em: 17 ago. 2022. -
APA
Traina Junior, C., Traina, A. J. M., & Figueiredo, J. M. de. (2004). Including conditional operators in content-based image retrieval in large sets of medical exams. In Proceedimgs. Los Alamitos: IEEE Computer Society. -
NLM
Traina Junior C, Traina AJM, Figueiredo JM de. Including conditional operators in content-based image retrieval in large sets of medical exams. Proceedimgs. 2004 ;[citado 2022 ago. 17 ] -
Vancouver
Traina Junior C, Traina AJM, Figueiredo JM de. Including conditional operators in content-based image retrieval in large sets of medical exams. Proceedimgs. 2004 ;[citado 2022 ago. 17 ] - Enhancing data visualization techniques
- DBM-tree: a dynamic metric access method sensitive to local density data
- Integrating images to patient electronic medical records through content-based retrieval techniques
- Enhanced visual evaluation of feature extractors for image mining
- Image domain formalization for content-based image retrieval
- Accelerating approximate similarity queries using genetic algorithms
- MAMView: a visual tool for exploring and understanding metric access methods
- Incluindo consultas por similaridade em SQL
- iDFQL: a query-based tool to help the teching process of the relational algebra
- Statistical association rules and relevance feedback
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