CODEWITHSUNDEEP
tensorflowloss-function
user12967451
user12967451

Reputation: 31

optimizing binary focal loss and dice loss

I am building a Unet image segmentation model with only one foreground and a background (binary segmentation).

For the loss function I sum the dice loss and binary focal loss

I am wondering if it is important to ensure the order of magnitude of dice loss and focal loss to be similar

As you see in the below extract, the binary focal loss is ~ 0.0x and the dice loss is in 0.x. will the loss optimization focus on the dice loss more than the focal loss in this case? Should i be adding a multiplier to the binary focal loss?

enter image description here

Upvotes: 0

Views: 1262

Answers (1)

user3411639
user3411639

Reputation: 51

I am a newbie to the deep learning paradigm as well. However, according to this paper: https://ieeexplore.ieee.org/abstract/document/9180275/ usually a multiplier must be added for a combo loss. In the paper the combo loss of focal loss and dice loss is calculated using the following equation: combo loss= β*focalloss - (log (dice loss)) Kindly report your results if you wish to use any other combination of these losses.

Upvotes: 0

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