How can U-Net accommodate for various input sizes?

It says in the lab description of U-Net that U-Net can accommodate for various input sizes. Why is this the case?

Hi Meir,

great question. Because it is an end-to-end fully convolutional network (FCN), i.e. it only contains Convolutional layers and does not contain any Dense layer, because of which it can accept image of any size.

I recommend that you read this article.

Happy learning,

Rosa

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In TensorFlow we need to create an Input layer and pass image size as an argument. So, in terms of implementation, how can we use variably sized training / test images without resizing them?

@arosacastillo

Rosa, many thanks for the article link. It is very well written and turned out to be quite useful! :+1:

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