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.

OverviewToolsMetricsAbout the catalogue
Contribute to the catalogue
Contribute to the catalogue

Mean Average Precision (MAP)

Website

Mean Average Precision (MAP) is a metric used to evaluate object detection models such as Fast R-CNN, YOLO, Mask R-CNN, etc. The mean of average precision(AP) values are calculated over recall values from 0 to 1.

Related use cases :

SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection

Uploaded on Mar 15, 2024
Language models (LMs) have proven to be powerful tools for psycholinguistic research, but most prior work has focused on purely behavioural measures (e.g., surprisal comparisons). ...

About the metric

You can click on the links to see the associated metrics

Objective(s):

Purpose(s):

Target sector(s):

Lifecycle stage(s):

Target users:

Risk management stage(s):

Modify this metric

catalogue Logos

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.