Train a Siamese Network to Compare Images with image size [227 227 3]

Hi,

I have followed the official tutorial to train Siamese Network to Compare Images

link: https://se.mathworks.com/help/deeplearning/ug/train-a-siamese-network-to-compare-images.html

The trained image of the network has a size of [105 105 1]. when I am trying to train a network on images with size [227 227 3] , I usually recieve many errors.

Can someone help which parts in the code need to be change?

Answer 1

[Sam Chak]

You should be able to find this line in the tutorial:

imageInputLayer([105 105 1],Normalization="none")

[MAHMOUD EID]

Hi sam,

Thanks for support.

I have done so on my image dataset and figured out where is the error. Usually the code runs only on the CPU.

-When choosing 'Auto' or 'GPU' , usually the code stop due to unsuffiecient memory in the GPU . I have tried to reduce the miniBatchSize to the minimuim number for example 4 or 5 , and still facing the same error. Do you have an idea tackling this isssue?

- the second point: During training, I notice that the loss during training is usually a fixed number (0.7) and not change across the 1000 iterations. I have tried to change learningRate = 6e-5;

gradDecay = 0.9;

gradDecaySq = 0.99;

but the losses during training not changing, what is supposed to change to reduce the losses during training?

@Sam Chak