Sparsey™: event recognition via deep hierarchical sparse distributed codes.

ABSTRACT: The visual cortex's hierarchical, multi-level organization is captured in many biologically inspired computational vision models, the general idea being that progressively larger scale (spatially/temporally) and more complex visual features are represented in progressively higher areas. However, most earlier models use localist representations (codes) in each representational field (which we equate with the cortical macrocolumn, "mac"), at each level. In localism, each represented feature/concept/event (hereinafter "item") is coded by a single unit. The model we describe, Sparsey, is hierarchical as well but crucially, it uses sparse distributed coding (SDC) in every mac in all levels. In SDC, each represented item is coded by a small subset of the mac's units. The SDCs of different items

SUBMITTER: Rinkus GJ 

PROVIDER: S-EPMC4266026 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature