This paper uses two different ways to generate features from an image: hand-crafted descriptors, which are predefined ways to find regions of interest and encode them into vectors; and neural features, automatically extracted and selected by an ImageNet pre-trained neural network.
the methods for visual representation investigated in this paper are: • Scale-Invariant Feature Transform (SIFT) (Lowe, 2004): This method extracts features that are invariant to scale, illumination and rotation.