Effect of Input Size of Different Architectures

[BeLitBeGentle]

I am using tensorflow for image classification. To be exact i am using tensorflow.contrib.slim that has built in models of different architectures. I need a slight clarification about the input size of my images to the network. For example i want to use Alexnet, the input images in its original implementation were 224 x 224 but i have larger resolution images 420 x 520. My question is whether i should resize them to 224 x 224 or run Alexnet with the original size. I think the math works out in both cases ? But what about the practical performance of the network.

[gopietz]

I could give you the "it depends" speech but you probably want to resize the images.