Thing you are talking about is similar to scene labeling (google the term and look at the pictures). Only you&#x27;d be doing it by hand, instead of letting NN find it&#x27;s own representation. This is good because you&#x27;d be creating a dataset full of regions that we could use to automatically segment the pictures into useful regions later.<p>There&#x27;s even a language mapping that you want, you want it to recognize image parts and associate it with a word, which also isn&#x27;t simple, because you&#x27;d have to have a lot of labels (candles, hands, hairs, cars, trees, licence plates etc.)<p>It is a harder problem than the one in the article.<p>State-of-the-art scene labeling is still not good enough (close to 80% accuracy) but I believe it&#x27;s due to lack of data because algorithms used combine neural networks with joint learning approaches such as conditional random fields to extract the regions.