Recommendation ITU-T P.565 provides the output of the framework which is a machine learning based speech quality prediction model that…

Recommendation ITU-T Y.3182 describes an intelligent cost-effective network management and orchestration framework that can cope with the challenges of multi-domain…

This Supplement presents the applications of machine learning (ML) in quantum key distribution networks (QKDNs). In particular, this Supplement includes:…

This Supplement analyses use cases for machine learning in future networks including IMT-2020, and presents them in a unified format.…

Supplement 37 to Recommendation ITU-T X.1231 defines a technical framework for countering spam based on machine learning (ML). It may…

Supplement 72 to ITU-T Y-series Recommendations provides the standardization roadmap for artificial intelligence (AI) in the field of information and…

Recommendation ITU-T M.3385 provides a detailed evaluation framework, evaluation rating method and automatic evaluating process for intelligence levels of systems…

Supplement 53 to ITU-T L-series Recommendations provides guidelines to policy-makers, technologists, innovators, environmentalists and other stakeholders from the technology industry,…

Big data as a service (BDaaS) is a cloud service category that provides cloud service customers with capabilities to collect,…

Connected vehicles are facing increasingly prominent network security issues along with their rapid development. Security threat information of connected vehicles,…

Recommendation ITU-T X.1377 establishes guidelines for an intrusion prevention system (IPS) for connected vehicles. This Recommendation mainly focuses on aspects…