Implementación y evaluación de un sistema de detección mediante la captura de imágenes para la clasificación de estrabismo, utilizando redes neuronales convolucionales
The diagnosis of strabismus, is very important to do in time during childhood, strabismus affects between 2% and 4% of the world population in children because this condition produces amblyopia, which consists of the loss of vision in the deviated eye, once developed the amblyopia, it cannot be trea...
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| Autores principales: | , |
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| Otros Autores: | |
| Formato: | Trabajo de grado (Pregrado y/o Especialización) |
| Lenguaje: | spa |
| Publicado: |
Universidad Antonio Nariño
2022
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| Materias: | |
| Acceso en línea: | http://repositorio.uan.edu.co/handle/123456789/6208 |
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| Sumario: | The diagnosis of strabismus, is very important to do in time during childhood,
strabismus affects between 2% and 4% of the world population in children because this
condition produces amblyopia, which consists of the loss of vision in the deviated eye, once
developed the amblyopia, it cannot be treated, because the brain inhibits the signal from the
deviated eye, resulting in the gradual and permanent loss of visual acuity in the affected
eye.Convolutional neural networks were used for this study, In order to detect strabismus in
patient images, the model used is DenseNet 201, an architecture designed for image
classification tasks, trained by a set of own images, acquired by the authors, consisting of
332 images. |
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