1. A method comprising: receiving, at a neural network, a subset of images of a plurality of images of a training image set; at the neural network, iteratively adjusting parameters of the neural network based on concurrent application of multiple loss functions to the subset of images, the multiple loss functions including a classification loss function and a hashing loss function, wherein the classification loss function is associated with an image classification function that extracts image features from an image, and wherein the hashing loss function is associated with a hashing function that generates a hash code associated with the image; and generating, at the neural network, a deep hash model based on the adjusted parameters of the neural network, the deep hash model including a deep hash model parameter.