Deep learning models for image classification: comparison and applications

S Sharma, K Guleria - 2022 2nd International Conference on …, 2022 - ieeexplore.ieee.org
Deep learning is the subfield of machine learning which performs data interpretation and
integrates several layers of features to produce prediction outcomes. It has a significant …

Biphasic majority voting-based comparative COVID-19 diagnosis using chest X-ray images

KM Sunnetci, A Alkan - Expert Systems with Applications, 2023 - Elsevier
The COVID-19 pandemic has been affecting the world since December 2019, and
nowadays, the number of infected is increasing rapidly. Chest X-ray images are clinical …

Boosting COVID-19 image classification using MobileNetV3 and aquila optimizer algorithm

M Abd Elaziz, A Dahou, NA Alsaleh, AH Elsheikh… - Entropy, 2021 - mdpi.com
Currently, the world is still facing a COVID-19 (coronavirus disease 2019) classified as a
highly infectious disease due to its rapid spreading. The shortage of X-ray machines may …

PrimePatNet87: prime pattern and tunable q-factor wavelet transform techniques for automated accurate EEG emotion recognition

A Dogan, M Akay, PD Barua, M Baygin, S Dogan… - Computers in Biology …, 2021 - Elsevier
Nowadays, many deep models have been presented to recognize emotions using
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …

An evolutionary crow search algorithm equipped with interactive memory mechanism to optimize artificial neural network for disease diagnosis

H Zamani, MH Nadimi-Shahraki - Biomedical Signal Processing and …, 2024 - Elsevier
Artificial neural network (ANN) is an information processing paradigm that loosely models
the thinking patterns of the human brain with specifications such as real-time learning, self …

An ensemble learning model for COVID-19 detection from blood test samples

OO Abayomi-Alli, R Damaševičius, R Maskeliūnas… - Sensors, 2022 - mdpi.com
Current research endeavors in the application of artificial intelligence (AI) methods in the
diagnosis of the COVID-19 disease has proven indispensable with very promising results …

White-box inference attack: compromising the security of deep learning-based COVID-19 diagnosis systems

BUH Sheikh, A Zafar - International Journal of Information Technology, 2024 - Springer
The COVID-19 pandemic has necessitated the exploration of innovative diagnostic
approaches, including the utilization of machine learning (ML) and deep learning (DL) …

Novel fuzzy deep learning approach for automated detection of useful COVID-19 tweets

SJ Malla, LK Kumar, PJA Alphonse - Artificial Intelligence in Medicine, 2023 - Elsevier
Abstract Coronavirus (COVID-19) is a newly discovered viral disease from the SARS-CoV-2
family. This has caused a moral panic resulting in the spread of informative and …

Word2vec neural model-based technique to generate protein vectors for combating COVID-19: a machine learning approach

TA Adjuik, D Ananey-Obiri - International Journal of Information …, 2022 - Springer
The world was ambushed in 2019 by the COVID-19 virus which affected the health,
economy, and lifestyle of individuals worldwide. One way of combating such a public health …

A survey of COVID-19 diagnosis using routine blood tests with the aid of artificial intelligence techniques

S Abbasi Habashi, M Koyuncu, R Alizadehsani - Diagnostics, 2023 - mdpi.com
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), causing a disease
called COVID-19, is a class of acute respiratory syndrome that has considerably affected the …