This standard defines terms related to artificial intelligence and associated technologies in health care including assistive intelligence, synthetic data, remote…
Vertical
ITU-T F.748.12
Deep learning software framework evaluation methodology
A deep learning software framework provides an easy and fast way for manufactures to develop their own artificial intelligence (AI)…
ISO 8000-66:2021
BS ISO 8000-66:2021
Data quality. Data quality management: Assessment indicators for data processing in manufacturing operations
What is ISO 8000‑66 about? ISO 8000‑66 discusses data quality management. ISO 8000‑66 specifies assessment indicators to support the assessment…
BS PAS 1882:2021
Data collection and management for automated vehicle trials for the purpose of incident investigation. Specification
What is PAS 1882:2021 about? Sponsored by the Centre for Connected and Autonomous Vehicles (CCAV) and building on the requirements…
This PAS gives recommendations for managing security risks that might lead to a compromise of safety in a connected automotive ecosystem. The PAS covers…
ETSI EG 203341 V 1.1.1
Core Network and Interoperability Testing (INT) – Approaches for Testing Adaptive Networks
The characteristics of ‘adaptive networks’ such as virtualization, self-organization, self-configuration, self-optimization, self-healing and self-learning offer huge advantages in future networks.…
AFNOR SPEC Z77-100-0
Contractualization of AI systems
ETSI TR 103748 V 1.1.1
Core Network and Interoperability Testing (INT) – Artificial Intelligence (AI) in Test Systems and Testing of AI Models – Use and Benefits of AI Technologies in Testing
The present document provides guidance on the use of AI technologies applied to testing. © Copyright 2023, ETSI
ITU-T L Supplement 52
Computer processing, data management and energy perspective
BSI Flex 1890 v4:2022-03
Connected and automated vehicles. Vocabulary
This document defines terms, initialisms and acronyms for the connected and automated vehicle (CAV) sector, focused on those relating to…
BS 10102-2:2020
Big data. Guidance on data-intensive projects
This part of BS 10102 provides guidance on good practice for implementing data-intensive projects to realize value, including: a) defining…
Recommendation ITU-T Y.3654 specifies the mechanisms of machine learning in big data driven networking (bDDN). A set of related aspects…
