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1 vote

Building a CNN (with Keras for pixelwise classification)

The last layer should match the dimension of your response. Dense layer can only return 1D whereas conv layers can return 2D., Based on your question, you want to classify all your pixels (binary?) in ...
Max's user avatar
  • 31
1 vote
Accepted

Why not using segmentation architectures for object detection?

At the end of the day, if an architecture satisfies your goal, you should use it. If you can detect objects using a segmentation model, go ahead. But that's where practice differs from theory. Don't ...
Valentin Calomme's user avatar
1 vote

My semantic segmentation model classifies everything as background

This answer might be a little late, but I believe that what you need is the Focal Tversky Loss (https://arxiv.org/abs/1810.07842). Neither the vanilla Focal Loss nor the Dice Loss generalize well for ...
mnobrecastro's user avatar

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