Inferring sparse, overcomplete image codes using an efficient coding framework · Contents. NIPS '97: Proceedings of the 1997 conference on Advances in neural ...

This paper applies mathematical analysis to a specific formalization of SCA using synthetic image models, hoping to gain insight into what might emerge from ...

Missing: Inferring | Show results with:Inferring

The sparse coding model works by finding a dictionary of basis functions such that only a few are needed to reconstruct any given image. Sparse coding was ...

We conclude that sparse coding can generate a suitable general representation for subsequent inference tasks.

This work describes a conceptually simple method for structured sparse coding and dictionary design. Supposing a dictionary with K atoms, we introduce a.

These sparse coding algorithms work directly on the objects, and are thus constrained to modeling only simple signals, e.g., aligned faces and digits. For ...

Missing: Inferring | Show results with:Inferring

This paper leverages a self-explanatory re- formulation of sparse representation, i.e., linking the learned dictionary atoms with the original feature spaces ...

The sparse coding model posits that the visual system has evolved to efficiently code natural stimuli using a sparse set of features from an overcomplete ...