Correcting data imbalance for semi-supervised covid-19 detection using x-ray chest images
A key factor in the fight against viral diseases such as the coronavirus (COVID-19) is the
identification of virus carriers as early and quickly as possible, in a cheap and efficient …
identification of virus carriers as early and quickly as possible, in a cheap and efficient …
Dealing with scarce labelled data: Semi-supervised deep learning with mix match for covid-19 detection using chest x-ray images
Coronavirus (Covid-19) is spreading fast, infecting people through contact in various forms
including droplets from sneezing and coughing. Therefore, the detection of infected subjects …
including droplets from sneezing and coughing. Therefore, the detection of infected subjects …
Dealing with distribution mismatch in semi-supervised deep learning for covid-19 detection using chest x-ray images: A novel approach using feature densities
In the context of the global coronavirus pandemic, different deep learning solutions for
infected subject detection using chest X-ray images have been proposed. However, deep …
infected subject detection using chest X-ray images have been proposed. However, deep …
Handling class imbalance in COVID-19 chest X-ray images classification: Using SMOTE and weighted loss
Healthcare systems worldwide have been struggling since the beginning of the COVID-19
pandemic. The early diagnosis of this unprecedented infection has become their ultimate …
pandemic. The early diagnosis of this unprecedented infection has become their ultimate …
A semi-supervised learning approach for COVID-19 detection from chest CT scans
COVID-19 has spread rapidly all over the world and has infected more than 200 countries
and regions. Early screening of suspected infected patients is essential for preventing and …
and regions. Early screening of suspected infected patients is essential for preventing and …
How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images
Over the past decade, the use of deep learning has been widely increasing in the medical
image diagnosis field. Deep learning-based methods'(DLMs) performance strongly relies on …
image diagnosis field. Deep learning-based methods'(DLMs) performance strongly relies on …
COVID-19 detection from chest X-Ray images using Deep Learning and Convolutional Neural Networks
The COVID-19 pandemic in 2020 has highlighted the need to pull all available resources
towards the mitigation of the devastating effects of such” Black Swan” events. Towards that …
towards the mitigation of the devastating effects of such” Black Swan” events. Towards that …
Variational autoencoder based imbalanced COVID-19 detection using chest X-ray images
S Chatterjee, S Maity, M Bhattacharjee… - New Generation …, 2023 - Springer
Early and fast detection of disease is essential for the fight against COVID-19 pandemic.
Researchers have focused on developing robust and cost-effective detection methods using …
Researchers have focused on developing robust and cost-effective detection methods using …
Transfer-to-transfer learning approach for computer aided detection of COVID-19 in chest radiographs
The coronavirus disease 2019 (COVID-19) global pandemic has severely impacted lives
across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities …
across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities …
Ensemble deep learning for the detection of covid-19 in unbalanced chest x-ray dataset
The ongoing COVID-19 pandemic has caused devastating effects on humanity worldwide.
With practical advantages and wide accessibility, chest X-rays (CXRs) play vital roles in the …
With practical advantages and wide accessibility, chest X-rays (CXRs) play vital roles in the …