Statistical Performance Metrics for Use with Imprecise Ground-Truth

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• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：9657
• 期：1
• 页码：31-44
• 丛书名：Graphic Recognition. Current Trends and Challenges
• ISBN：978-3-319-52159-6
• 卷排序：9657

文摘

This paper addresses performance evaluation in the presence of imprecise ground-truth. Indeed, the most common assumption when performing benchmarking measures is that the reference data is flawless. In previous work, we have shown that this assumption cannot be taken for granted, and that, in the case of perceptual interpretation problems it is most certainly always wrong but for the most trivial cases.