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Mostrando ítems 1-6 de 6
Artículo
Dual Machine-Learning system to aid Glaucoma Diagnosis using disc and cup feature extraction.
(IEEE Computer Society, 2020)
Glaucoma is a degenerative disease that affects vision, causing damage to the optic nerve that ends in vision loss. The classic techniques to detect it have undergone a great change since the intrusion of machine learning ...
Ponencia
Multidataset Incremental Training for Optic Disc Segmentation
(Springer, 2020)
When convolutional neural networks are applied to image segmentation results depend greatly on the data sets used to train the networks. Cloud providers support multi GPU and TPU virtual machines making the idea of ...
Artículo
A study on the use of Edge TPUs for eye fundus image segmentation
(Elsevier, 2021)
Medical image segmentation can be implemented using Deep Learning methods with fast and efficient segmentation networks. Single-board computers (SBCs) are difficult to use to train deep networks due to their memory and ...
Artículo
TPU Cloud-Based Generalized U-Net for Eye Fundus Image Segmentation
(IEEE Computer Society, 2019)
Medical images from different clinics are acquired with different instruments and settings. To perform segmentation on these images as a cloud-based service we need to train with multiple datasets to increase the ...
Ponencia
Deep learning glaucoma diagnosis aid
(3 ciencias. Área de Innovación y Desarrollo,S.L., 2019)
El glaucoma es una de las principales causas de ceguera. Cambia la morfología del nervio óptico. La copa es la región central del disco óptico. El CDR (relación del diámetro de la copa y el disco) es un indicador del ...
Ponencia
Multi-dataset Training for Medical Image Segmentation as a Service
(ScitePress Digital Library, 2019)
Deep Learning tools are widely used for medical image segmentation. The results produced by these techniques depend to a great extent on the data sets used to train the used network. Nowadays many cloud service providers ...