Mean average precision is a metric used to evaluate the performance of object recognition systems by measuring the accuracy of predicted bounding boxes against ground truth labels. It combines both precision and recall into a single score, offering insight into how well an algorithm identifies and localizes objects within images. This metric is particularly useful in tasks where both the classification of objects and their precise locations are crucial.
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