[HTML][HTML] A comparative study of X-ray and CT images in COVID-19 detection using image processing and deep learning techniques
The deadly coronavirus has not just devastated the lives of millions but has put the entire
healthcare system under tremendous pressure. Early diagnosis of COVID-19 plays a …
healthcare system under tremendous pressure. Early diagnosis of COVID-19 plays a …
Fourier-Bessel representation for signal processing: A review
Several applications, analysis and visualization of signal demand representation of time-
domain signal in different domains like frequency-domain representation based on Fourier …
domain signal in different domains like frequency-domain representation based on Fourier …
An efficient multi-thresholding based COVID-19 CT images segmentation approach using an improved equilibrium optimizer
Optimization is the process of searching for the optimal (best-so-far) solution among a wide
range of solutions. Besides, in the last two decades, a family of algorithms known as …
range of solutions. Besides, in the last two decades, a family of algorithms known as …
FBSED based automatic diagnosis of COVID-19 using X-ray and CT images
PK Chaudhary, RB Pachori - Computers in Biology and Medicine, 2021 - Elsevier
This work introduces the Fourier-Bessel series expansion-based decomposition (FBSED)
method, which is an implementation of the wavelet packet decomposition approach in the …
method, which is an implementation of the wavelet packet decomposition approach in the …
COVID-19 disease identification from chest CT images using empirical wavelet transformation and transfer learning
In the current scenario, novel coronavirus disease (COVID-19) spread is increasing day-by-
day. It is very important to control and cure this disease. Reverse transcription-polymerase …
day. It is very important to control and cure this disease. Reverse transcription-polymerase …
Quantitative and qualitative analysis of 18 deep convolutional neural network (CNN) models with transfer learning to diagnose COVID-19 on chest X-ray (CXR) …
LS Chow, GS Tang, MI Solihin, NM Gowdh… - SN Computer …, 2023 - Springer
Abstract Coronavirus disease 2019 (COVID-19) is a disease caused by a novel strain of
coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), severely …
coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), severely …
An efficient deep learning method for detection of COVID-19 infection using chest X-ray images
The research community has recently shown significant interest in designing automated
systems to detect coronavirus disease 2019 (COVID-19) using deep learning approaches …
systems to detect coronavirus disease 2019 (COVID-19) using deep learning approaches …
Automatic diagnosis of covid-19 from ct images using cyclegan and transfer learning
The outbreak of the corona virus disease (COVID-19) has changed the lives of most people
on Earth. Given the high prevalence of this disease, its correct diagnosis in order to …
on Earth. Given the high prevalence of this disease, its correct diagnosis in order to …
Multi-strategy ant colony optimization for multi-level image segmentation: Case study of melanoma
D Zhao, A Qi, F Yu, AA Heidari, H Chen, Y Li - … Signal Processing and …, 2023 - Elsevier
Melanoma, which results from the cancerous transformation of melanocytes, is the most
dangerous skin cancer in the medical field. Today, image processing technology has been …
dangerous skin cancer in the medical field. Today, image processing technology has been …
The effect of deep feature concatenation in the classification problem: an approach on COVID‐19 disease detection
In image classification applications, the most important thing is to obtain useful features.
Convolutional neural networks automatically learn the extracted features during training …
Convolutional neural networks automatically learn the extracted features during training …