Documentos de Areiza-Laverde H.J. | REDI

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Mostrando 3 resultados de: 3

Filtros aplicados

Palabras Claves: "Machine Learning"

Subtipo de publicación

Conference Object(2)

Publisher

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(1)

Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics(1)

Proceedings of SPIE - The International Society for Optical Engineering(1)

Proceedings of SPIE the International Society for Optical Engineering(1)

Sensors (Switzerland)(1)

Área temáticas

Enfermedades(2)

Biblioteconomía y Documentación informatica(1)

Cirugía y especialidades médicas afines(1)

Fisiología humana(1)

Funcionamiento de bibliotecas y archivos(1)

Área de conocimiento

Aprendizaje automático(2)

Laboratorio médico(1)

Objetivos de Desarrollo Sostenible

ODS 17: Alianzas para lograr los objetivos(3)

ODS 3: Salud y bienestar(3)

ODS 9: Industria, innovación e infraestructura(3)

Año de Publicación

Origen

Palabras Claves

Automatic classification(1)

Multimodality(1)

A novel method for objective selection of information sources using multi-kernel SVM and local scaling

Abstract: Advancement on computer and sensing technologies has generated exponential growth in the data availa

Palabras claves:

Machine Learning, Multimodality, multiple kernel learning, Source selection, SUPPORT VECTOR MACHINES

A. E. Castro-Ospina, Areiza-Laverde H.J., Díaz G.M., Hernández M.L.

Breast Lesion Discrimination Using Saliency Features from MRI Sequences and MKL-Based Classification

Conference Object

Abstract: Breast MRI interpretation requires that radiologists examine several images, depending on the acquis

Palabras claves:

Breast MRI, GBVS, Machine Learning, MKL, Visual saliency

A. E. Castro-Ospina, Areiza-Laverde H.J., Díaz G.M., Duarte-Salazar C.a., Hernández M.L.

Radiomics-based differentiation of pleomorphic adenomas and Warthin tumors of salivary glands

Conference Object

Abstract: Pleomorphic adenomas (PA) and Warthin tumors (WT) are the most common salivary gland tumors. It exhi

Palabras claves:

Automatic classification, Machine Learning, magnetic resonance imaging, Pleomorphic adenoma, Radiomics, Warthin tumor

A. E. Castro-Ospina, Areiza-Laverde H.J., Brea B., Díaz G.M., Malpica-González N.