Described herein are computer-implemented systems, methods, and apparatuses for predicting classifications for image data, the system comprising a processor, memory and storage, and configured to: receive at least one image data sample; generate, using a deep neural network, for each image data sample, an activation layer comprising a set of activation vectors; perform activation vector correspondence for at least one of the activation vectors based on activation vector distance and conditioned by non-image data; and predict at least one classification for each image data sample based on the activation vector correspondence.