Hey! I don’t think people usually replace the first layer of a network but rather the last layers. The first part of AlexNet is convolutional so it should be able to handle your whole images.
It’s the fully connected layers at the end that won’t match in dimensions, so you could replace them. They are easier to train than the first layer due to the nature of backprop anyway.
Another idea would to change your model to a fully convolutional one, then you wouldn’t have to replace the last few layers - but one solution would be to add a single layer at the end.