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Progress in Biomedical Optics and Imaging - Proceedings of SPIE(2)
IISE Annual Conference and Expo 2018(1)
Neural Networks(1)
Neurocomputing(1)
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Medicina y salud(4)
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AdaEn-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:googlescopusResU-Net: Residual convolutional neural network for prostate MRI segmentation
Conference ObjectAbstract: The identification and segmentation of the prostate on magnetic resonance images (MRI) can assist inPalabras claves:convolutional neural networks, deep learning, image segmentation, medical image processingAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopus