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ITU-T L Supplement 53
Guidelines on the implementation of environmental efficiency criteria for artificial intelligence and other emerging technologies
Supplement 53 to ITU-T L-series Recommendations provides guidelines to policy-makers, technologists, innovators, environmentalists and other stakeholders from the technology industry,…
IEEE 2941.2
IEEE Standard for Application Programming Interfaces (APIs) for Deep Learning (DL) Inference Engines
A set of application programming interfaces (APIs) that is aimed at breaking down the barriers between different deep learning (DL)…
IEEE 3161
IEEE Standard for Digital Retina Systems
The aspects of reference architecture, technical characteristics, components, and functional requirements of digital retina systems for real-time analysis and processing…
VDI/VDE 3714 Blatt 4
Implementation and operation of big data applications in the manufacturing industry – Analysis process classes
Although the term “Big Data” has been used for several years, it continues to be associated with very different topics…
VDI/VDE 3714 Blatt 3
Implementation and operation of big data applications in the manufacturing industry – Data management
Although the term “Big Data” has been used for several years, it continues to be associated with very different topics…
Share your thoughts on this standard with the AI Standards Hub community here.
Share your thoughts on this standard with the AI Standards Hub community here.
Share your thoughts on this standard with the AI Standards Hub community here.
Share your thoughts on this standard with the AI Standards Hub community here.
Share your thoughts on this standard with the AI Standards Hub community here.
Share your thoughts on this standard with the AI Standards Hub community here.
Recommendation ITU-T Y.3183 provides a framework for machine learning-assisted network slicing management, leveraging vertical end users’ feedback on quality of…
