为什么要使用骰子系数而不是IOU来进行细分任务? [英] Why Dice Coefficient and not IOU for segmentation tasks?
问题描述
我见过人们使用 IOU
作为检测
任务的度量标准,并且使用 Dice Coeff
作为 segmentation
任务的度量标准.就骰子而言,这两个度量看起来非常相似,不同的是骰子给相交部分赋予两倍的权重.如果我没错,那么
I have seen people using IOU
as the metric for detection
tasks and Dice Coeff
for segmentation
tasks. The two metrics looks very much similar in terms of equation except that dice gives twice the weightage to the intersection part. If I am correct, then
Dice: (2 x (A*B) / (A + B))
IOU : (A * B) / (A + B)
是否有特定的原因更喜欢使用骰子进行细分,而使用IOU进行检测?
Is there any particular reason for preferring dice for segmentation and IOU for detection?
推荐答案
这不完全正确.
Dice系数(也称为Sørensen–Dice系数和F1得分)定义为A和B的交集面积的两倍,再除以A和B的面积之和:
The Dice coefficient (also known as the Sørensen–Dice coefficient and F1 score) is defined as two times the area of the intersection of A and B, divided by the sum of the areas of A and B:
Dice = 2 |A∩B| / (|A|+|B|) = 2 TP / (2 TP + FP + FN)
(TP =真阳性,FP =假阳性,FN =假阴性)
(TP=True Positives, FP=False Positives, FN=False Negatives)
IOU(联合上的交集,也称为Jaccard索引)定义为交集的面积除以联合的面积:
The IOU (Intersection Over Union, also known as the Jaccard Index) is defined as the area of the intersection divided by the area of the union:
Jaccard = |A∩B| / |A∪B| = TP / (TP + FP + FN)
请注意,A和B的面积之和与A和B的并集面积不同.特别是,如果有100%的重叠,则一个是另一个的两倍.这是Dice系数中两次"的原因:它们都被定义为在100%重叠时值为1,在0%重叠时值为0.
Note that the sum of the areas of A and B is not the same as the area of the union of A and B. In particular, if there is 100% overlap, then the one is twice the other. This is the reason of the "two times" in the Dice coefficent: they are both defined such that, with 100% overlap, the values are 1, and with 0% overlap the values are 0.
使用哪个取决于每个领域的个人喜好和习俗.您看到一个人在一个领域中使用更多的机会与机会相关,而不是其他任何因素.有人开始使用Dice系数进行细分,而其他人则紧随其后.有人开始使用IOU进行检测,而其他人则紧随其后.
Which one to use depends on personal preference and customs in each field. That you see one used more in one field is related more to chance than anything else. Someone started using the Dice coefficient for segmentation, and other people just followed along. Someone started using IOU for detection, and other people just followed along.
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