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Deep learning: systematic review, models, challenges, and research directions
T Talaei Khoei, H Ould Slimane… - Neural Computing and …, 2023 - Springer
The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …
automation applications. This automation transition can provide a promising framework for …
Backbones-review: Feature extractor networks for deep learning and deep reinforcement learning approaches in computer vision
To understand the real world using various types of data, Artificial Intelligence (AI) is the
most used technique nowadays. While finding the pattern within the analyzed data …
most used technique nowadays. While finding the pattern within the analyzed data …
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 …
Machine learning applications for COVID-19 outbreak management
Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted
practically every area of human life. Several machine learning (ML) approaches are …
practically every area of human life. Several machine learning (ML) approaches are …
Detection of Covid-19 and other pneumonia cases from CT and X-ray chest images using deep learning based on feature reuse residual block and depthwise dilated …
G Celik - Applied Soft Computing, 2023 - Elsevier
Covid-19 has become a worldwide epidemic which has caused the death of millions in a
very short time. This disease, which is transmitted rapidly, has mutated and different …
very short time. This disease, which is transmitted rapidly, has mutated and different …
GCDN-Net: Garbage classifier deep neural network for recyclable urban waste management
The escalating waste volume due to urbanization and population growth has underscored
the need for advanced waste sorting and recycling methods to ensure sustainable waste …
the need for advanced waste sorting and recycling methods to ensure sustainable waste …
COVID-19 classification using chest X-ray images based on fusion-assisted deep Bayesian optimization and Grad-CAM visualization
The COVID-19 virus's rapid global spread has caused millions of illnesses and deaths. As a
result, it has disastrous consequences for people's lives, public health, and the global …
result, it has disastrous consequences for people's lives, public health, and the global …
A multi-objective segmentation method for chest X-rays based on collaborative learning from multiple partially annotated datasets
Accurate segmentation of multiple targets, such as ribs, clavicles, heart, and lung fields, from
chest X-ray images is crucial for diagnosing various lung diseases. Currently, mainstream …
chest X-ray images is crucial for diagnosing various lung diseases. Currently, mainstream …
A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
ABSTRACT The Coronavirus (COVID-19) outbreak in December 2019 has drastically
affected humans worldwide, creating a health crisis that has infected millions of lives and …
affected humans worldwide, creating a health crisis that has infected millions of lives and …
RADIC: A tool for diagnosing COVID-19 from chest CT and X-ray scans using deep learning and quad-radiomics
O Attallah - Chemometrics and Intelligent Laboratory Systems, 2023 - Elsevier
Deep learning (DL) algorithms have demonstrated a high ability to perform speedy and
accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The …
accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The …