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 …

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 …

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 …

Deep neural networks (DNNs) have produced state-of-the-art results in many benchmarks
and problem domains. However, the success of DNNs depends on the proper configuration …

Abstract Convolutional Neural Networks (CNNs) are frequently used for image classification.
This is crucial for the biomedical image classification used for automatic diagnosis in …

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 …

Deep learning is an essential method of machine learning. Deep learning is rapidly suitable
for the most sophisticated stage of a technology, prominent to enriched performance in …

Abstract Deep Convolutional Neural Networks (DCNNs) have the potential to revolutionize
the field of Medical Imaging Diagnostics due to their capabilities of learning by using only …

Deep neural networks (DNNs) have proven to be effective at solving challenging problems,
but their success relies on finding a good architecture to fit the task. Designing a DNN …