Coronavirus disease (COVID-19) detection in chest X-ray images using majority voting based classifier ensemble
Abstract Novel coronavirus disease (nCOVID-19) is the most challenging problem for the
world. The disease is caused by severe acute respiratory syndrome coronavirus-2 (SARS …
world. The disease is caused by severe acute respiratory syndrome coronavirus-2 (SARS …
Pneumonia detection in chest X-ray images using convolutional neural networks and transfer learning
A large number of children die due to pneumonia every year worldwide. An estimated 1.2
million episodes of pneumonia were reported in children up to 5 years of age, of which …
million episodes of pneumonia were reported in children up to 5 years of age, of which …
[HTML][HTML] Compressive strength and elastic modulus of RBAC: an analysis of existing data and an artificial intelligence based prediction
L Lin, J Xu, J Yuan, Y Yu - Case Studies in Construction Materials, 2023 - Elsevier
In recent years crushing waste brick to produce recycled brick aggregates (RBAs) has
become a viable solution for reducing environmental pollution and addressing the natural …
become a viable solution for reducing environmental pollution and addressing the natural …
Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images
Chest X-ray images are used in deep convolutional neural networks for the detection of
COVID-19, the greatest human challenge of the 21st century. Robustness to noise and …
COVID-19, the greatest human challenge of the 21st century. Robustness to noise and …
A self-activated cnn approach for multi-class chest-related COVID-19 detection
Chest diseases can be dangerous and deadly. They include many chest infections such as
pneumonia, asthma, edema, and, lately, COVID-19. COVID-19 has many similar symptoms …
pneumonia, asthma, edema, and, lately, COVID-19. COVID-19 has many similar symptoms …
Automatic detection of tuberculosis related abnormalities in Chest X-ray images using hierarchical feature extraction scheme
Abstract Machine learning techniques have been widely used for abnormality detection in
medical images. Chest X-ray images (CXR) are among the non-invasive diagnostic tools …
medical images. Chest X-ray images (CXR) are among the non-invasive diagnostic tools …
[HTML][HTML] An optimized and efficient android malware detection framework for future sustainable computing
Android-based smart devices cater to services in almost every aspect of our lives like
personal, professional, social, banking, business, etc. However, people with increasingly …
personal, professional, social, banking, business, etc. However, people with increasingly …
Disease localization and severity assessment in chest X-ray images using multi-stage superpixels classification
Abstract Background and Objectives Chest X-ray (CXR) is a non-invasive imaging modality
used in the prognosis and management of chronic lung disorders like tuberculosis (TB) …
used in the prognosis and management of chronic lung disorders like tuberculosis (TB) …
[HTML][HTML] A three-stage ensemble boosted convolutional neural network for classification and analysis of COVID-19 chest x-ray images
S Kalaivani, K Seetharaman - International Journal of Cognitive Computing …, 2022 - Elsevier
For the identification and classification of COVID-19, this research presents a three-stage
ensemble boosted convolutional neural network model. A conventional segmentation model …
ensemble boosted convolutional neural network model. A conventional segmentation model …
Intelligent intrusion detection scheme for smart power-grid using optimized ensemble learning on selected features
The smart grid has gained a reputation as the advanced paradigm of the power grid. It is a
complicated cyber-physical system that combines information and communication …
complicated cyber-physical system that combines information and communication …