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 …
Explainable artificial intelligence approach in combating real-time surveillance of COVID19 pandemic from CT scan and X-ray images using ensemble model
Population size has made disease monitoring a major concern in the healthcare system,
due to which auto-detection has become a top priority. Intelligent disease detection …
due to which auto-detection has become a top priority. Intelligent disease detection …
Mrl-net: Multi-scale representation learning network for covid-19 lung ct image segmentation
S Liu, T Cai, X Tang, C Wang - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
Accuracy segmentation of COVID-19 lesions in lung CT images can aid patient screening
and diagnosis. However, the blurred, inconsistent shape and location of the lesion area …
and diagnosis. However, the blurred, inconsistent shape and location of the lesion area …
Adjusting logit in Gaussian form for long-tailed visual recognition
It is not uncommon that real-world data are distributed with a long tail. For such data, the
learning of deep neural networks becomes challenging because it is hard to classify tail …
learning of deep neural networks becomes challenging because it is hard to classify tail …
Exploratory parallel hybrid sampling framework for imbalanced data classification
M Zheng, Z Zhao, F Wang, X Hu, S Xu, W Li… - … Applications of Artificial …, 2024 - Elsevier
Current engineering application scenarios often face the challenge of imbalanced data,
hybrid sampling is an effective method to deal with the imbalanced data classification issue …
hybrid sampling is an effective method to deal with the imbalanced data classification issue …
A Siamese neural network-based diagnosis of COVID-19 using chest X-rays
Radiological findings play an essential and complementary role in diagnosing Covid-19,
assessing its severity, and managing its patients. Artificial intelligence technology based on …
assessing its severity, and managing its patients. Artificial intelligence technology based on …
Utilizing Artificial Intelligence and IoT Technologies for Enhanced COVID-19 Diagnosis
The rapid spread of COVID-19 and the high mortality toll globally necessitated an immediate
reaction from several industries to provide an early illness forecast. As a result, the Internet …
reaction from several industries to provide an early illness forecast. As a result, the Internet …
ASD: Towards attribute spatial decomposition for prior-free facial attribute recognition
Representing the spatial properties of facial attributes is a vital challenge for facial attribute
recognition (FAR). Recent advances have achieved the reliable performances for FAR …
recognition (FAR). Recent advances have achieved the reliable performances for FAR …
Καταπολέμηση της ανισορροπίας των κλάσεων με τη χρήση των Conditional GANs στην ιατρική απεικόνιση για τη διάγνωση της πνευμονίας
Η Ζαμπετάκης - 2024 - dione.lib.unipi.gr
Η αποτελεσματική διαχείριση των ιατρικών δεδομένων είναι σημαντική για τη διασφάλιση της
αξιοπιστίας των συστημάτων ανίχνευσης με τη βοήθεια υπολογιστή (computer-aided …
αξιοπιστίας των συστημάτων ανίχνευσης με τη βοήθεια υπολογιστή (computer-aided …
Adversarial Training Classifier for Imbalanced and Semi-Supervised Learning
W Liu, M Chen, R Chen - 2023 China Automation Congress …, 2023 - ieeexplore.ieee.org
The imbalanced learning research has made great progress due to the introduction of
generative adversarial networks (GANs). However, most studies focus on combining GAN …
generative adversarial networks (GANs). However, most studies focus on combining GAN …