Mean Average Precision (MAP)

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.

Trustworthy AI Relevance

This metric addresses Robustness, Safety by quantifying relevant system properties. MAP supports the Robustness objective because it quantifies how well an AI model maintains accurate detection or ranking performance, which reflects resilience and reliability under typical conditions. By providing a clear performance benchmark, it indirectly contributes to Safety by helping identify models that perform reliably and thus reduce risks of harmful or erroneous outputs.