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 …

Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …

Offline Arabic Handwriting Recognition (OAHR) has recently become instrumental in the
areas of pattern recognition and image processing due to its application in several fields …

Convolutional neural networks (CNNs) have shown outstanding results in different
application tasks. However, the best performance is obtained when customized CNNs …

For the early diagnosis of lung cancer, radiologists assisted computer-aided detection (CAD)
systems are used. The false-positive reduction (FPR) is important in feature representation …

Deep convolutional neural networks (DCNNs) have achieved surpassing success in the
field of computer vision, and a number of elaborately designed networks refresh the …

Much has been said about the fusion of bio-inspired optimization algorithms and Deep
Learning models for several purposes: from the discovery of network topologies and …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

Automated machine learning (AutoML) is a young research area aiming at making high-
performance machine learning techniques accessible to a broad set of users. This is …