I would like to have a superficial idea about the methods used by Google to perform image annotation and how these methods are related to each other. I couldn't find anywhere else this information, except some user's guesses, and I would like to have something more reliable.
Thank you
I believe much of the API's backend is done with tensorflow. (https://cloud.google.com/blog/big-data/2016/05/explore-the-galaxy-of-images-with-cloud-vision-api, https://cloud.google.com/blog/big-data/2016/02/google-cloud-vision-api-available-to-all)
--> I'm guessing that there's some big ol' deep convolutional neural networks trained from google images, implemented with tensorflow (https://www.tensorflow.org/, http://kaptur.co/what-googles-new-open-source-tensorflow-and-cloud-vision-api-mean-for-photo-app-developers/).
Some tensorflow info about deep convolutional neural networks: https://www.tensorflow.org/versions/r0.9/tutorials/image_recognition/index.html