Deep learning approaches have demonstrated great achievements in the field of computer-
aided medical image analysis, improving the precision of diagnosis across a range of …

Agricultural productivity plays a vital role in global economic development and growth. When
crops are affected by diseases, it adversely impacts a nation's economic resources and …

Artificial intelligence technologies such as machine learning and deep learning employ
techniques to anticipate results more effectively without human involvement. Since AI …

Carbon fiber reinforced polymer (CFRP) composites have been continuously replacing
conventional metallic materials due to their excellent material properties. The orthotropic …

A crucial element in the diagnosis of breast cancer is the utilization of a classification method
that is efficient, lightweight, and precise. Convolutional neural networks (CNNs) have …

The misleading information during the coronavirus disease 2019 (COVID‐19) pandemic's
peak time is very sensitive and harmful in our community. Analyzing and detecting COVID …

Segmentation of myocardial infarction (MI) is a crucial task in the field of heart disease
theranostics. Cardiac magnetic resonance imaging (MRI) is a well-known non-invasive …

Abstract In this research, Attention Induced Multi-head Convolutional Neural Network
Organization using MobileNetv1 Transfer Learning and COVID-19 Diagnosis using Jellyfish …

Breast cancer is a prevalent global disease where early detection is crucial for effective
treatment and reducing mortality rates. To address this challenge, a novel Computer-Aided …

This study systematically reviews CNN-based medical image classification methods. We
surveyed 149 of the latest and most important papers published to date and conducted an in …