Cargando…
A Deep Batch Normalized Convolution Approach for Improving COVID-19 Detection from Chest X-ray Images
Pre-trained machine learning models have recently been widely used to detect COVID-19 automatically from X-ray images. Although these models can selectively retrain their layers for the desired task, the output remains biased due to the massive number of pre-trained weights and parameters. This pape...
Autores principales: | Al-Shourbaji, Ibrahim, Kachare, Pramod H., Abualigah, Laith, Abdelhag, Mohammed E., Elnaim, Bushra, Anter, Ahmed M., Gandomi, Amir H. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860560/ https://www.ncbi.nlm.nih.gov/pubmed/36678365 http://dx.doi.org/10.3390/pathogens12010017 |
Ejemplares similares
-
An efficient churn prediction model using gradient boosting machine and metaheuristic optimization
por: AlShourbaji, Ibrahim, et al.
Publicado: (2023) -
Detecting Pneumonia Using Convolutions and Dynamic Capsule Routing for Chest X-ray Images
por: Mittal, Ansh, et al.
Publicado: (2020) -
Convolutional neural networks for the classification of chest X-rays in the IoT era
por: Almezhghwi, Khaled, et al.
Publicado: (2021) -
Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks
por: Sharma, Neetan, et al.
Publicado: (2023) -
Effective Utilization of Multiple Convolutional Neural Networks for Chest X-Ray Classification
por: Rammuni Silva, Ravidu Suien, et al.
Publicado: (2022)