Mostrando 6 resultados de: 6
Filtros aplicados
Publisher
Communications in Computer and Information Science(3)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(2)
Sensors (Switzerland)(1)
Characterizing ResNet Filters to Identify Positive and Negative Findings in Breast MRI Sequences
Conference ObjectAbstract: Training of deep learning models requires large and properly labeled datasets, which make unfeasiblePalabras claves:Breast Cancer, Deep feature selection, multiple kernel learning, ResNet, Transfer learningAutores:A. E. Castro-Ospina, Díaz G.M., Hernández M.L., Marín-Castrillón D.M., Osorno-Castillo K.Fuentes:scopusAutomatic BI-RADS description of mammographic masses
Conference ObjectAbstract: This paper presents a CBIR (Content Based Information Retrieval) framework for automatic descriptionPalabras claves:Automatic annotation, BI-RADS, Computer Aided Diagnosis, Content-based Image RetrievalAutores:Díaz G.M., Fabián R. Narváez, Romero E.Fuentes:googlescopusBreast Lesion Discrimination Using Saliency Features from MRI Sequences and MKL-Based Classification
Conference ObjectAbstract: Breast MRI interpretation requires that radiologists examine several images, depending on the acquisPalabras claves:Breast MRI, GBVS, Machine learning, MKL, Visual saliencyAutores:A. E. Castro-Ospina, Areiza-Laverde H.J., Díaz G.M., Duarte-Salazar C.a., Hernández M.L.Fuentes:scopusA novel method for objective selection of information sources using multi-kernel SVM and local scaling
ArticleAbstract: Advancement on computer and sensing technologies has generated exponential growth in the data availaPalabras claves:Machine learning, Multimodality, multiple kernel learning, Source selection, SUPPORT VECTOR MACHINESAutores:A. E. Castro-Ospina, Areiza-Laverde H.J., Díaz G.M., Hernández M.L.Fuentes:scopusFeature group selection using mkl penalized with ℓ<inf>1</inf> -norm and svm as base learner
Conference ObjectAbstract: Objective feature selection is an important component in the machine learning framework, which has aPalabras claves:feature selection, Group LASSO, Multimodality, multiple kernel learning, sparsityAutores:A. E. Castro-Ospina, Areiza-Laverde H.J., Díaz G.M.Fuentes:scopusMachine learning methods for classifying mammographic regions using the wavelet transform and radiomic texture features
Conference ObjectAbstract: Automatic detection and classification of lesions in mammography remains one of the most important aPalabras claves:Breast Cancer, Machine learning methods, Radiomics, ROI classificationAutores:A. E. Castro-Ospina, Díaz G.M., Fabián R. Narváez, Rincón J.S.Fuentes:googlescopus