Mostrando 5 resultados de: 5
Filtros aplicados
Publisher
Progress in Biomedical Optics and Imaging - Proceedings of SPIE(3)
Neural Networks(1)
Neurocomputing(1)
Área temáticas
Ciencias de la computación(3)
Enfermedades(3)
Física aplicada(2)
Métodos informáticos especiales(2)
C-MADA: Unsupervised Cross-Modality Adversarial Domain Adaptation framework for Medical Image Segmentation
Conference ObjectAbstract: Deep learning models have obtained state-of-the-art results for medical image analysis. However, CNNPalabras claves:Domain Adaptation, Generative Adversarial Networks, image segmentation, Medical image analysis, unsupervised learningAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusAdaEn-Net: An ensemble of adaptive 2D–3D Fully Convolutional Networks for medical image segmentation
ArticleAbstract: Fully Convolutional Networks (FCNs) have emerged as powerful segmentation models but are usually desPalabras claves:deep learning, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusAdaResU-Net: Multiobjective adaptive convolutional neural network for medical image segmentation
ArticleAbstract: Adapting an existing convolutional neural network architecture to a specific dataset for medical imaPalabras claves:convolutional neural networks, deep learning, Evolutionary algorithms, Hyperparameter optimization, Medical image segmentation, Multiobjective optimizationAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusEMONAS: Efficient multiobjective neural architecture search framework for 3D medical image segmentation
Conference ObjectAbstract: Deep learning plays a critical role in medical image segmentation. Nevertheless, manually designingPalabras claves:deep learning, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusSelf-adaptive 2D-3D ensemble of fully convolutional networks for medical image segmentation
Conference ObjectAbstract: Segmentation is a critical step in medical image analysis. Fully Convolutional Networks (FCNs) havePalabras claves:deep learning, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopus