Name
Abstract | ||
|---|---|---|
Visual position and orientation orders are discussed in two forms. At phenomenological level, position and orientation orders are explicitly expressed in an energy model. Several kinds of perceptual binding emerge as global solutions to this energy model. A new regularization theory is presented to use position and orientation orders. This regularization theory provides a general approach to visual representation and learning. |
Year | DOI | Venue |
|---|---|---|
1997 | null | 1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4 |
Keywords | Field | DocType |
shape,neural nets,pattern recognition,automation,neurophysiology,liquid crystals,visual perception,machine vision | Computer vision,Neurophysiology,Artificial intelligence,Artificial neural network,Regularization theory,Perception,Mathematics,Visual perception | Conference |
Volume | Issue | ISSN |
1 | null | null |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiyong Yang | 1 | 0 | 0.68 |
| Songde Ma | 2 | 2 | 0.98 |