Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

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) applications. However, different frameworks show different performances under different scenarios. Recommendation ITU-T F.748.12 helps to evaluate deep learning software frameworks to help manufactures take full advantage of certain frameworks and avoid the disadvantages of others. © ITU 2023All Rights Reserved

The information about this standard has been compiled by the AI Standards Hub, an initiative dedicated to knowledge sharing, capacity building, research, and international collaboration in the field of AI standards. You can find more information and interactive community features related to this standard by visiting the Hub’s AI standards database here. To access the standard directly, please visit the developing organisation’s website.

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.