Are CNNs "less attentive" at image edges than in the middle?

In my image classification task, all image areas can provide hints, but some crucial information is right at the edge. Is it a concern? Every conv layer has padding, but I’m unsure if it is difficult for CNNs to extract information right from the image edge. Surely, I could pad the whole input image, but that would add computational and memory cost, too.

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I wouldn’t think this would be a problem, as long as you’re getting some information from the edges.

However, the best way to find out is to try! Run some experiments and see if you get any difference.