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BEMD-3DCNN-based method for COVID-19 detection
Ali Riahi
,
Omar Elharrouss
, Somaya Al-Maadeed
Research output
:
Contribution to journal
›
Article
›
peer-review
27
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Citations (Scopus)
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Keyphrases
3D Convolutional Neural Network (3D CNN)
100%
3D Representation
20%
Attention Module
40%
Attention Network
20%
Better Performance
20%
Contextual Attention
60%
Contextual Information
40%
Coronavirus Outbreak
20%
COVID-19
100%
Decomposition Method
20%
Deep Learning Model
20%
DenseNet
20%
Detection Performance
20%
Detection System
20%
Diagnostic System
20%
Experiment Results
20%
Feature Map
40%
First Day
20%
Fully Connected Layer
20%
Information Processing
20%
Medical Imaging Techniques
20%
Multivariate Empirical Mode Decomposition
100%
Original Image
20%
Pneumonia
20%
Rapid Detection
20%
Rapid Diagnostic Test
20%
ResNet
20%
Robust Detection
20%
Spatial Data
20%
Virus
60%
Visual Geometry Group-16 (VGG16)
20%
Wuhan China
20%
X-ray Images
20%
Computer Science
Attention (Machine Learning)
20%
Contextual Information
40%
COVID-19
100%
Deep Learning Model
20%
DenseNet
20%
Detection Performance
20%
empirical mode decomposition
100%
Feature Map
40%
Fully Connected Layer
20%
Information Processing
20%
Medical Imaging
20%
Residual Neural Network
20%
Spatial Information
20%
Vertebral Column
80%
VGG-16
20%
Earth and Planetary Sciences
China
50%
Deep Learning Model
50%
Imaging Technique
50%
Information Processing
50%
International Monetary Fund
100%
Medical Science
50%
X Ray
50%
Physics
Resnet
33%