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 …

Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …

Abstract Deep Neural Networks (DNNs) are widely regarded as the most effective learning
tool for dealing with large datasets, and they have been successfully used in thousands of …

As an advanced artificial intelligence technique for solving learning problems, deep learning
(DL) has achieved great success in many real-world applications and attracted increasing …

Deep neural networks have been shown to outperform classical machine learning
algorithms in solving real-world problems. However, the most successful deep neural …

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 …

Network intrusion detection system (NIDS) is a commonly used tool to detect attacks and
protect networks, while one of its general limitations is the false positive issue. On the basis …

Swarm intelligence algorithms have been widely adopted in solving many highly nonlinear,
multimodal problems and have achieved tremendous successes. However, their application …

Deep learning (DL) has become an important machine learning approach that has been
widely successful in many applications. Currently, DL is one of the best methods of …

Deep neural networks (DNNs), which are extensions of artificial neural networks, can learn
higher levels of feature hierarchy established by lower level features by transforming the raw …