How can I tune loss functions for better segmentation results?
An example of an AI chatbot conversation about tuning loss functions for image segmentation tasks.
How can I tune loss functions for better segmentation results?
Tuning loss functions is crucial for improving segmentation performance. Are you using a specific model or framework?
I'm using U-Net for medical image segmentation.
Great choice! You might want to experiment with Dice loss or Focal loss, as they can handle class imbalance well.
How do I implement Dice loss in my U-Net model?
You can implement Dice loss by defining a custom loss function in your training script. Would you like a code example?
Yes, please! That would be really helpful.
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