Cargando…
Stacking Ensemble and ECA-EfficientNetV2 Convolutional Neural Networks on Classification of Multiple Chest Diseases Including COVID-19
RATIONALE AND OBJECTIVES: Early detection and treatment of COVID-19 patients is crucial. Convolutional neural networks have been proven to accurately extract features in medical images, which accelerates time required for testing and increases the effectiveness of COVID-19 diagnosis. This study prop...
Autores principales: | Huang, Mei-Ling, Liao, Yu-Chieh |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association of University Radiologists. Published by Elsevier Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748720/ https://www.ncbi.nlm.nih.gov/pubmed/36526533 http://dx.doi.org/10.1016/j.acra.2022.11.027 |
Ejemplares similares
-
EfficientNetV2 Based Ensemble Model for Quality Estimation of Diabetic Retinopathy Images from DeepDRiD
por: Tummala, Sudhakar, et al.
Publicado: (2023) -
An Improved EfficientNetV2 Model Based on Visual Attention Mechanism: Application to Identification of Cassava Disease
por: Ye, Yuanbo, et al.
Publicado: (2022) -
Stacked ensemble learning based on deep convolutional neural networks for pediatric pneumonia diagnosis using chest X-ray images
por: Prakash, J. Arun, et al.
Publicado: (2022) -
A Smartphone-Based Detection System for Tomato Leaf Disease Using EfficientNetV2B2 and Its Explainability with Artificial Intelligence (AI)
por: Debnath, Anjan, et al.
Publicado: (2023) -
A storage-efficient ensemble classification using filter sharing on binarized convolutional neural networks
por: Kim, HyunJin, et al.
Publicado: (2022)