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I fail to understand the evaluation parameters like true positive, false positive and false negative in detection and classification tasks.

can anyone help me to figure out what does each of these parameters mean? Can anyone please give an example?

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The detection task is: Given an image $I$, does it contain a sub-image $S$ (or an object $S$)?

There are several things that can happen:

  • $I$ contains $S$ and the detector says $I$ contains $S$

    • This is a True Positive: the statement is true, and the statement is positive ($S$ is there)
  • $I$ contains $S$ and the detector says $I$ DOES NOT contain $S$

    • This is a False Negative: the statement is false, and the statement is negative ($S$ is NOT there)
  • $I$ DOES NOT contain $S$ and the detector says $I$ DOES NOT contain $S$

    • This is a True Negative: the statement is true, and the statement is negative ($S$ is NOT there)
  • $I$ DOES NOT contain $S$ and the detector says $I$ contains $S$

    • This is a False Positive: the statement is false, and the statement is positive ($S$ is there)
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