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COVID-19 image classification using deep learning: Advances, challenges and opportunities
Abstract Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
Application of deep learning techniques in diagnosis of covid-19 (coronavirus): a systematic review
Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth
century. Covid-19 has already endangered the lives of millions of people worldwide due to …
century. Covid-19 has already endangered the lives of millions of people worldwide due to …
On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
[HTML][HTML] Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
Lung cancer (LC) remains a leading cause of death worldwide. Early diagnosis is critical to
protect innocent human lives. Computed tomography (CT) scans are one of the primary …
protect innocent human lives. Computed tomography (CT) scans are one of the primary …
A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset
This paper aims to propose a high-speed and accurate fully-automated method to detect
COVID-19 from the patient's chest CT scan images. We introduce a new dataset that …
COVID-19 from the patient's chest CT scan images. We introduce a new dataset that …
COVID-19 lung CT image segmentation using deep learning methods: U-Net versus SegNet
Background Currently, there is an urgent need for efficient tools to assess the diagnosis of
COVID-19 patients. In this paper, we present feasible solutions for detecting and labeling …
COVID-19 patients. In this paper, we present feasible solutions for detecting and labeling …
Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Applications of artificial intelligence in battling against covid-19: A literature review
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …
COVID-19 CT image synthesis with a conditional generative adversarial network
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread
rapidly since December 2019. Real-time reverse transcription polymerase chain reaction …
rapidly since December 2019. Real-time reverse transcription polymerase chain reaction …
Hyperspectral pathology image classification using dimension-driven multi-path attention residual network
Hyperspectral imaging technology (HSI) can capture pathological tissue's spatial and
spectral information simultaneously, with wide coverage and high accuracy characteristics …
spectral information simultaneously, with wide coverage and high accuracy characteristics …