Classification of chest diseases using deep learning
The field of computer vision has had exponential progress in a wide range of applications due to the use of deep learning and especially the existence of large annotated image data sets [1]. Significant improvements have been shown in the performance of problems previously considered difficult, such...
- Autores:
-
Silva, Jesús
Zilberman, Jack
Pinillos-Patiño, Yisel
Varela Izquierdo, Noel
Pineda, Omar
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7278
- Acceso en línea:
- https://hdl.handle.net/11323/7278
https://repositorio.cuc.edu.co/
- Palabra clave:
- ChestX-ray8
Classification of chest diseases
Deep learning
- Rights
- closedAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
| Summary: | The field of computer vision has had exponential progress in a wide range of applications due to the use of deep learning and especially the existence of large annotated image data sets [1]. Significant improvements have been shown in the performance of problems previously considered difficult, such as object recognition, detection and segmentation over approaches based on obtaining the characteristics of the image by hand [2]. This article presents a novel method for the classification of chest diseases in the standard and widely used data set ChestX-ray8, which contains more than 100,000 front view images with 8 diseases. |
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