Throughout the centuries, nature has been a source of inspiration, with much still to learn
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …

Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …

Medical data widely exist in the hospital and personal life, usually across institutions and
regions. They have essential diagnostic value and therapeutic significance. The disclosure …

The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …

The identification of ore deposits is an important technical task in mining and excavation.
However, conventional techniques are time-consuming and tedious. Therefore, data …

Deep neural networks (DNNs) have evolved as a beneficial machine learning method that
has been successfully used in various applications. Currently, DNN is a superior technique …

The early detection of breast cancer is a vital factor when it comes to improving cure and
recovery rates in patients. Among such early detection factors, one finds thermography, an …

This paper presents a content-based image retrieval technique that focuses on extraction
and reduction in multiple features. To obtain multi-level decomposition of the image by …

This study proposes a novel bioinspired metaheuristic simulating how the coronavirus
spreads and infects healthy people. From a primary infected individual (patient zero), the …

Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …