This standard defines terms related to artificial intelligence and associated technologies in health care including assistive intelligence, synthetic data, remote…
AI-specific
DIN DKE SPEC 99001
Definition of a success method for labelling data for artificial intelligence training – Application focus: Question-Answering; Text in English
VDE-AR-E 2842-61-1
Development and trustworthiness of autonomous/cognitive systems – Part 61-1: Terms and concepts
VDE-AR-E 2842-61-1 specifies a general framework for the development of trustworthy solutions and trustworthy autonomous / cognitive systems, including the…
VDE-AR-E 2842-61-2
Development and trustworthiness of autonomous/cognitive systems – Part 61-2: Management
This VDE application guide “Development and Trustworthiness of autonomous / cognitive Systems – Part 2: Management”describes the requirements for the…
VDE-AR-E 2842-61-3
Development and Trustworthiness of autonomous/cognitive Systems – Part 61-3: Development at Solution Level (whole application)
This VDE application guide, Development and Trustworthiness of autonomous/cognitive Systems – Part 3: Development at Solution Level (whole application) describes…
Today, companies must evolve their products and services, which creates a pool of new projects in a context of increasing…
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)…
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…
ITU-T L.1305
Data centre infrastructure management system based on big data and artificial intelligence technology
This Recommendation describes specifications of a data centre infrastructure management (DCIM) system based on big data and artificial intelligence (AI)…
ISO/IEC AWI 27090
Cybersecurity — Artificial Intelligence — Guidance for addressing security threats and failures in artificial intelligence systems
This document provides guidance for organizations to address security threats and failures in artificial intelligence (AI) systems. The guidance in…
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
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.…
