<p>It is not necessary that the input size of the CNN should be the same as that of the training data.</p>

<p>What input size to choose depends on what application you are using the CNN for. For example, for classification, a 32x32 image might give a good accuracy. But for something like segmentation, it will most probably not give a good output. That being said, using a higher resolution image will result in a slightly higher accuracy. Refer this <a href="https://arxiv.org/abs/1501.02876" rel="nofollow">paper</a>. So, if you afford the extra processing time, go for the higher resolution.</p>
Ideal input size of CNN given training data
<p>Should the input size of the CNN follow that of the training data ? For example, if my training data is of size 192 x 98 then what should the input size of my CNN be ? 192 x 192 ? 98 x 98 ? Would it be a bad idea if I use a 32x32 input CNN ?</p>

<p>I have sooooo many questions on the specifics of CNN but no one has the answer.</p>