Object detectors output detection bounding boxes along with confidence scores. The higher the score, the more confident the model is that the associated bounding box is a correct detection.
When used in applications (like this one), the user typically establishes a confidence threshold and then every detection above that threshold is treated as a positive detection, the rest are discarded. The choice can be arbitrary or (sorta) principled.
sorokod
Ok, then "prediction score" is the confidence score? And the confidence threshold for an artefact being a yurt is 40%?
When used in applications (like this one), the user typically establishes a confidence threshold and then every detection above that threshold is treated as a positive detection, the rest are discarded. The choice can be arbitrary or (sorta) principled.