I always see that the width and height of the kernel are the same. But is it a good idea to use different numbers?
Recently I tried to use GoogLeNet (which expects images to be 224x224) on my images (500x150) and I got an error:
Negative dimension size caused by subtracting 7 from 5 for 'average_pooling2d_5/AvgPool'...
I know that this error is because the height of my image is too small. If I use the height of about 200, then everything is ok. So, maybe, in this situation, I could just use a smaller height and bigger width in the kernel. For example (5, 3).
Is it a good idea in this case? Or in general? How can it affect the accuracy of the network and the ability to extract different features?