Vision transformers in medical computer vision—A contemplative retrospection

A Parvaiz, MA Khalid, R Zafar, H Ameer, M Ali… - … Applications of Artificial …, 2023 - Elsevier
Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …

Conventional and novel diagnostic tools for the diagnosis of emerging SARS-CoV-2 variants

VP Chavda, DD Valu, PK Parikh, N Tiwari, AS Chhipa… - Vaccines, 2023 - mdpi.com
Accurate identification at an early stage of infection is critical for effective care of any
infectious disease. The “coronavirus disease 2019 (COVID-19)” outbreak, caused by the …

Deepsign: Sign language detection and recognition using deep learning

D Kothadiya, C Bhatt, K Sapariya, K Patel… - Electronics, 2022 - mdpi.com
The predominant means of communication is speech; however, there are persons whose
speaking or hearing abilities are impaired. Communication presents a significant barrier for …

Design and analysis of a deep learning ensemble framework model for the detection of COVID-19 and pneumonia using large-scale CT scan and X-ray image …

X Xue, S Chinnaperumal, GM Abdulsahib, RR Manyam… - Bioengineering, 2023 - mdpi.com
Recently, various methods have been developed to identify COVID-19 cases, such as PCR
testing and non-contact procedures such as chest X-rays and computed tomography (CT) …

Segmentation-based classification deep learning model embedded with explainable AI for COVID-19 detection in chest X-ray scans

N Sharma, L Saba, NN Khanna, MK Kalra, MM Fouda… - Diagnostics, 2022 - mdpi.com
Background and Motivation: COVID-19 has resulted in a massive loss of life during the last
two years. The current imaging-based diagnostic methods for COVID-19 detection in …

[HTML][HTML] Diagnosis of COVID-19 from X-rays using combined CNN-RNN architecture with transfer learning

MM Islam, MZ Islam, A Asraf, MS Al-Rakhami… - BenchCouncil …, 2022 - Elsevier
Combating the COVID-19 pandemic has emerged as one of the most promising issues in
global healthcare. Accurate and fast diagnosis of COVID-19 cases is required for the right …

An efficient deep learning model to detect COVID-19 using chest X-ray images

S Chakraborty, B Murali, AK Mitra - International Journal of Environmental …, 2022 - mdpi.com
The tragic pandemic of COVID-19, due to the Severe Acute Respiratory Syndrome
coronavirus-2 or SARS-CoV-2, has shaken the entire world, and has significantly disrupted …

TOPSIS aided ensemble of CNN models for screening COVID-19 in chest X-ray images

R Pramanik, S Dey, S Malakar, S Mirjalili, R Sarkar - Scientific Reports, 2022 - nature.com
Abstract The novel coronavirus (COVID-19), has undoubtedly imprinted our lives with its
deadly impact. Early testing with isolation of the individual is the best possible way to curb …

Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics

PM Khaniabadi, Y Bouchareb, H Al-Dhuhli… - Computers in biology …, 2022 - Elsevier
Objective To develop a two-step machine learning (ML) based model to diagnose and
predict involvement of lungs in COVID-19 and non COVID-19 pneumonia patients using CT …

LSTM-autoencoder for vibration anomaly detection in vertical carousel storage and retrieval system (VCSRS)

JS Do, AB Kareem, JW Hur - Sensors, 2023 - mdpi.com
Industry 5.0, also known as the “smart factory”, is an evolution of manufacturing technology
that utilizes advanced data analytics and machine learning techniques to optimize …