What does a confidence percentage indicate in computer vision?

A confidence percentage in computer vision reflects how certain the AI is about its prediction regarding an image or a task it is performing. In this context, when a computer vision model outputs a confidence score, it quantifies the level of certainty associated with its classification or identification of objects within an image. For instance, if a model indicates a confidence percentage of 90% for identifying a cat, it means that the model is 90% certain that the image contains a cat.

This confidence metric is essential for understanding the reliability of the model's predictions. It allows developers and users to make informed decisions based on the AI's output, such as whether to accept or verify the prediction further. In applications such as autonomous driving, medical imaging, or security systems, knowing the confidence level can significantly influence operational responses and safety measures.

The other choices do not accurately describe what confidence percentage signifies. Analyzed images pertain to input quantity, processing speed relates to performance efficiency, and feature detection is more about the AI's input analysis rather than the certainty of its predictions.