Can we change the input size of a pretrained network for transfer learning

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I want to use transfer learning on the Resnet-50 architecture trained on Imagenet. I noticed that the input size into the Resnet-50 architecture is [224 224 3]. However my images are [150 150 3]. I was wondering if there were a way to change the input size of the input layer rather than resizing my images.
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Pakize
Pakize on 26 Dec 2021
I have a same question. As far as I understand, we can only resize the images, but not change the input layer as we change the output layers.

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Answers (1)

BERGHOUT Tarek
BERGHOUT Tarek on 16 Apr 2019
yes this methode is cold:
1- if you are changing the neumber of neurons from N to n where N>n: this is called :'constructive' learning
2- if you are changing the neumber of neurons from N to n where N<n: this is called :'distructive' learning
but retraining alwayse requeired , not from the begining but from the final weights that u have in final net
if you want to found some papaers in this area use this key words :
neural networks with additive hidden nodes ; distructive neural nets .....etc. good luck.
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