What's the current ML pet method for multi-label image classification? It seems like you could string together a bunch of individual classifiers e.g. "Scene contains dog", "Scene contains cat", but is there an efficient (and effective) way of doing it in one go? Does it significantly increase the complexity of the network? I would imagine a cat detector would be far simpler than a cat and/or dog detector.