Suppose someone wanted to train a model to identify which decade a photo was taken in. What would be the current SOTA architecture for that type of task? (Suppose also that you had a few million labeled examples.)
I like yolo because it’s a production grade object defector. It seems harder to find a production grade classifier.
One amusing but dumb idea would be to use yolo for this: train the model on “photo from 1930,” “photo from 1940,” etc, where the bounding boxes cover the entire photo. But I’m curious what the professional solution might be.
I like yolo because it’s a production grade object defector. It seems harder to find a production grade classifier.
One amusing but dumb idea would be to use yolo for this: train the model on “photo from 1930,” “photo from 1940,” etc, where the bounding boxes cover the entire photo. But I’m curious what the professional solution might be.