Cargando…
A bagging dynamic deep learning network for diagnosing COVID-19
COVID-19 is a serious ongoing worldwide pandemic. Using X-ray chest radiography images for automatically diagnosing COVID-19 is an effective and convenient means of providing diagnostic assistance to clinicians in practice. This paper proposes a bagging dynamic deep learning network (B-DDLN) for dia...
Autores principales: | Zhang, Zhijun, Chen, Bozhao, Sun, Jiansheng, Luo, Yamei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8358001/ https://www.ncbi.nlm.nih.gov/pubmed/34381079 http://dx.doi.org/10.1038/s41598-021-95537-y |
Ejemplares similares
-
Bag of Tricks for Improving Deep Learning Performance on Multimodal Image Classification
por: Adeshina, Steve A., et al.
Publicado: (2022) -
Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image
por: Nwosu, Lucy, et al.
Publicado: (2022) -
Random-Forest-Bagging Broad Learning System With Applications for COVID-19 Pandemic
Publicado: (2021) -
Deep learning-based monitoring technique for real-time intravenous medication bag status
por: Hwang, Young Jun, et al.
Publicado: (2023) -
Diagnosing COVID-19 from CT Image of Lung Segmentation & Classification with Deep Learning Based on Convolutional Neural Networks
por: Kumari, K. Sita, et al.
Publicado: (2021)