Have you published that paper anywhere on a conference or so? I guess not because it's not really in the common format. But from a quick look, it actually looks

Have you published that paper anywhere on a conference or so? I guess not because it's not really in the common format. But from a quick look, it actually looks interesting, so why not try to submit it somewhere, e.g. some image conference? But you really should work on the format. I assume that this was not done with LaTeX? Then, in the table in your experimental results, what you are also comparing is number of parameters, and maybe train time, and inference time, and maybe memory consumption during inference, so that should all be also in the table. Also, there should be one or two figures which give small sketches of your models blocks, which helps to better understand the difference to e.g. XCeption. Also, as I understand, QuickNet is mostly based on XCeption? But XCeption is not in the table of your experimental comparisons. Also you mention MobileNets which is also not there. You should add that. Then, if you additionally add compression methods like 8-bit quantization, you should have a separate table where you show how much less memory it needs and how much it degrades the performance. Then, to really boost interest in your paper, it would be really nice if you publish some code. It sounds like you already implemented that in Lasagne or in Keras? So just publish that code.