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- Junmei Zhu
- ICANN
- 2008

We present a correspondence-based system for visual object recognition with invariance to position, orientation, scale and deformation. The system is intermediate between high- and low-dimensional representations of correspondences. The essence of the approach is based on higher-order links, called here maplets, which are specific to narrow ranges of… (More)

We investigate a possible functional role of glial cells as information routing devices of the cerebral cortex. On the one hand, functionally motivated models of neural information processing were lately suggested which rely on short-term changes of connections between neural modules to dynamically route neural activity. Although successful in practice, the… (More)

One way to handle the perception of images that change in position (or size, orientation or deformation) is to invoke rapidly changing fiber projections to project images into a fixed format in a higher corti-cal area. We propose here a model for the ontogenesis of the necessary control structures. For simplicity we limit ourselves to fiber projections… (More)

The goal of the visual correspondence problem is to establish a connectivity pattern (a mapping) between two images such that features projected from the same scene point are connected. Dynamic Link Matching (DLM) is a self-organizing dy-namical system to establish such connectivity patterns for object recognition, but with rather naturally given simple… (More)

We here are pointing out a basically well-known pathway to the analysis of self-organizing systems that is now well in reach of numerical methods. Systems of coupled nonlinear differential equations are decomposed into normal modes, are reduced by adiabatic elimination of stable modes to a much smaller system of unstable modes and their nonlin-ear… (More)

Perceptual systems often have to disentangle different factors from mixed observations. If each factor is represented by a set of variables, each standing for a discrete value of the factor, the factor values underlying an observation can be extracted by a winner-take-all (WTA) mechanism over the direct product of the factors. Search in the product space,… (More)

- Junmei Zhu
- IJCNN
- 2010

— Winner-take-all (WTA) networks are ubiquitous in computational models of the brain. A WTA system determines its largest input. If the input space is the product of multiple factors, search in the product space can be expensive, in which case it is computationally attractive to work on the marginal factors. In this paper we study the organization of two… (More)

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