Convolutional neural networks (CNNs) are deep learning models used widely for solving
various tasks like computer vision and speech recognition. CNNs are developed manually …

Abstract Convolutional Neural Networks (CNNs) have demonstrated their superiority in
image classification, and evolutionary computation (EC) methods have recently been …

The COVID-19 pandemic has changed the way we practice medicine. Cancer patient and
obstetric care landscapes have been distorted. Delaying cancer diagnosis or maternal-fetal …

During the last decade, deep neural networks have shown a great performance in many
machine learning tasks such as classification and clustering. One of the most successful …

Evolutionary algorithms have been successfully employed to find the best structure for many
learning algorithms including neural networks. Due to their flexibility and promising results …

Recently, convolutional neural networks (CNNs) have shown promising achievements in
various computer vision tasks. However, designing a CNN model architecture necessitates a …

Convolutional neural networks (CNN) are highly effective for image classification and
computer vision activities. The accuracy of CNN architecture depends on the design and …

Convolutional neural networks (CNNs), among the deep learning models, are making
remarkable progress in a variety of computer vision tasks, such as image recognition …

Convolutional neural network has demonstrated high performance in many real-world
problems in recent years. However, the results and accuracy of a CNN that are applied for a …

Convolutional neural networks (CNNs) are one of the most effective deep learning methods
to solve image classification problems, but the design of the CNN architectures is mainly …