Babenko et al. apply convolutional neural networks to image retrieval. In particular, the architecture proposed by Krizhevsky et al.  (shown in Figure 1), has been used to compute features for image retrieval. They experimented with different layers, dimensionality reduction techniques (e.g. PCA and Large-Margin Dimensionality Reduction ), and both the pre-trained model and a refined model to demonstrate state-of-the-art performance on many image retrieval datasets.