Our data set was from surveys collected for human use using a variety of digital cameras - not DSLRs though. The surveyors did take specific images, blurry imag

Our data set was from surveys collected for human use using a variety of digital cameras - not DSLRs though. The surveyors did take specific images, blurry images would have meant not getting paid so none of those. We used transfer learning from the imagenet network vs a few hundred of the images well labelled and we trained it on a 6 gpu machine (titan x's) This is no place to claim results or do the detailed write up so all I would say is that do try for yourself if you haven't already, I was shocked by the quality of the classifier. Maybe you will be too! I started from the dataset bias position myself - billions of family snaps and selfies can't provide the reference for arbitrary images of stuff from arbitrary angles. My reading of the results that we got is that the claims of lower level features extracted by the cnn are correct, and that a network trained on massive public data can be the basis for specialised tools trained on more constrained proprietary datasets. Your milage may vary though...