… , deep learning (DL) is becoming a powerful method to add intelligence to wireless networks
… DL uses many neural network layers to achieve a brain-like acute feature extraction from …

… As such, in this article we propose an auto-learning framework to achieve intelligent and
automatic network optimization by using machine learning (ML) techniques. We review the …

… The authors created DeepDR, a deep neural network model, then trained it to learn the
genetic background of tumors based on data from The Cancer Genome Atlas (TCGA). DeepDR …

… Utilizing artificial intelligence (AI) expertise, especially machine and deep learning solutions…
on IoT security intelligence, which is built on machine and deep learning technologies that …

… so they rely heavily on edge and core networks to manage, process, and analyze data. As
a … development of intelligent and effective resource management and network management …

… New intelligent network solutions are evolving because answers to telecommunications
needs in the past no longer respond to requirements. Just a few years ago, the feeling among …

… of computer-supported collaborative learning (CSCL). … /or intelligent systems that aim to
support collaborative learning (eg, [2]) (a detailed analysis of the design and impact of intelligent …

… Similar to learning in biological systems, neural network learning involves adjustments to
the synaptic connections that exist between the neurons. Probabilistic models and fuzzy logic …

… learning, modeling, optimization, and data representation. Moreover, in COBANETS, we
propose to combine this learning architecture with the emerging network … the learning approach. …

… of web-based intelligent e-learning technology. In recent years, network-based teaching
and learning has become widespread, with bespoke solutions by individual institutions and …