I agree that using an ImageNet-trained model to classify a new set of subclasses should be easy, and is. Subsequent lessons show how to adapt the same approach to distinguishing dog breeds (more specific), and for identifying types of terrain in satellite images, which bear much less resemblance to anything in ImageNet.

That last one sounds pretty similar to your second sentence. Given what we know about transfer learning and CNN's, if we had a massive boat dataset, I bet it could be re-purposed to do pretty well at cat/dog.