mdfwn / segmentation-experiment Goto Github PK
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Using Keras (U-Net architecture) to segment shapes on noise.
I was wondering why you are using UpSampling2D vs Conv2DTranspose for a semantic segmentation task.
In keras, UpSampling2D is a simple resizing while Conv2DTranspose is the layer known as "deconvolutional" layer.
was there a reason for that?
Best regards
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