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scopus(10)
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:googlescopusAn extensive pixel-level augmentation framework for unsupervised cross-modality domain adaptation
OtherAbstract: Convolutional neural networks (CNNs) have achieved great success in automating the segmentation of mPalabras claves:Autores:Maria G. Baldeon CalistoFuentes:googleA Multi-object Deep Neural Network Architecture to detect Prostate Anatomy in T2-weighted MRI: Performance Evaluation
OtherAbstract: We present a 2D-3D convolutional neural network (CNN) ensemble automatically constructed to segmentPalabras claves:Autores:Maria G. Baldeon CalistoFuentes:googleCrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation
OtherAbstract: Domain Adaptation (DA) has recently been of strong interest in the medical imaging community. WhilePalabras claves:Domain Adaptation, segmentation, Vestibular schwannomaAutores:Bakas S., Batmanghelich K., Belkov A., Cardoso J., Choi J.W., Dawant B.M., Dong H., Dorent R., Escalera S., Fan Y., Glocker B., Hansen L., Heinrich M.P., Ivory M., Joshi S., Joutard S., Kashtanova V., Kim H.G., Kondo S., Kruse C.N., Kujawa A., Lai-Yuen S.K., Li H., Liu H., Ly B., Maria G. Baldeon Calisto, Modat M., Oguz I., Ourselin S., Rieke N., Shapey J., Shin H., Shirokikh B., Su Z., Vercauteren T., Wang G., Wu J., Xu Y., Yao K., Zhang L.Fuentes:googlescopusCOVID-19 ResNet: Residual neural network for COVID-19 classification with three-step Bayesian optimization
OtherAbstract: COVID-19 is an infectious disease caused by a novel coronavirus called SARS-CoV-2. The first case apPalabras claves:Autores:Maria G. Baldeon CalistoFuentes:googleApplication of Machine Learning algorithms for the pbkp_rediction of payment by agreement in a debt collection company with the CRISP-DM methodology
OtherAbstract: Debt collection from a debt collection agency (DCA) has become more difficult due to the pandemic. NPalabras claves:Autores:Maria G. Baldeon CalistoFuentes:googleAdaEn-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:googlescopusAnálisis estadístico de accidentalidad laboral del Ecuador y comparación con la accidentalidad laboral de Colombia del año 2013
OtherAbstract: La accidentalidad laboral trae consigo altos costos humanos, sociales y económicos a la sociedad, alPalabras claves:Autores:Maria G. Baldeon CalistoFuentes:googleEMONAS-Net: Efficient multiobjective neural architecture search using surrogate-assisted evolutionary algorithm for 3D medical image segmentation
ArticleAbstract: Deep learning plays a critical role in medical image segmentation. Nevertheless, manually designingPalabras claves:AutoML, convolutional neural networks, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopus