This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …

Abstract Space biology research aims to understand fundamental spaceflight effects on
organisms, develop foundational knowledge to support deep space exploration and …

Recognising handwritten digits or characters is a challenging task due to noisy data that
results from different writing styles. Numerous applications essentially motivate to build an …

This study makes a comprehensive assessment of the predominant Transfer Learning (TL)
techniques employed for the classification of COVID-19 cases in Chest X-rays (CXR) …

Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning
systems to assist clinicians and improve interpretation accuracy. An understanding of the …

Recent infectious disease outbreaks, such as the COVID-19 pandemic and the Zika
epidemic in Brazil, have demonstrated both the importance and difficulty of accurately …

This study provides a review of CNN's ensemble learning method for transfer learning by
highlighting sections such as review studies, datasets, pre-trained models, transfer learning …

This literature review summarizes the current deep learning methods developed by the
medical imaging AI research community that have been focused on resolving lung imaging …

Biomedical Instrumentation is one of the fastest health emerging innovative technologies
with proven contribution towards interdisciplinary medicine, it helps physicians to diagnose …

Disease severity identification using computational intelligence-based approaches is
gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches …