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Compute the variation of dice coefficient loss for real-value
regression task, such as super resolution. Mathematically,
Loss = (2x^Ty+e)/(x^Tx+y^Ty+e)
where x,y
are both vectors in float32. e
referes to smooth term (default 1).
layer {
name: "loss"
type: "DiceCoefLoss"
bottom: "Deconv"
bottom: "label"
top: "loss"
}
The usage is the same as EuclideanLoss
layer, restricted to bottom_size==2
.
Unet Dice Loss for segmentation:
Dice(A,B) = 2|AB|/(|A|+|B|)
Source Code: