Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

L Alzubaidi, J Zhang, AJ Humaidi, A Al-Dujaili… - Journal of big Data, 2021 - Springer
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …

Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19

F Shi, J Wang, J Shi, Z Wu, Q Wang… - IEEE reviews in …, 2020 - ieeexplore.ieee.org
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world.
Medical imaging such as X-ray and computed tomography (CT) plays an essential role in …

Automated detection of COVID-19 cases using deep neural networks with X-ray images

T Ozturk, M Talo, EA Yildirim, UB Baloglu… - Computers in biology …, 2020 - Elsevier
Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of
China in December 2019, spread rapidly around the world and became a pandemic. It has …

Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks

A Narin, C Kaya, Z Pamuk - Pattern Analysis and Applications, 2021 - Springer
The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread
rapidly among people living in other countries and is approaching approximately …

Covid-net: A tailored deep convolutional neural network design for detection of covid-19 cases from chest x-ray images

L Wang, ZQ Lin, A Wong - Scientific reports, 2020 - nature.com
Abstract The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a
devastating effect on the health and well-being of the global population. A critical step in the …

Inf-net: Automatic covid-19 lung infection segmentation from ct images

DP Fan, T Zhou, GP Ji, Y Zhou, G Chen… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to
face an existential health crisis. Automated detection of lung infections from computed …

Covid-ct-dataset: a ct scan dataset about covid-19

X Yang, X He, J Zhao, Y Zhang, S Zhang… - arxiv preprint arxiv …, 2020 - arxiv.org
During the outbreak time of COVID-19, computed tomography (CT) is a useful manner for
diagnosing COVID-19 patients. Due to privacy issues, publicly available COVID-19 CT …

Classification of the COVID-19 infected patients using DenseNet201 based deep transfer learning

A Jaiswal, N Gianchandani, D Singh… - Journal of …, 2021 - Taylor & Francis
Deep learning models are widely used in the automatic analysis of radiological images.
These techniques can train the weights of networks on large datasets as well as fine tuning …

COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images

F Ucar, D Korkmaz - Medical hypotheses, 2020 - Elsevier
Abstract The Coronavirus Disease 2019 (COVID-19) outbreak has a tremendous impact on
global health and the daily life of people still living in more than two hundred countries. The …

Covid-caps: A capsule network-based framework for identification of covid-19 cases from x-ray images

P Afshar, S Heidarian, F Naderkhani… - Pattern Recognition …, 2020 - Elsevier
Abstract Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the
world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely …