Name
Abstract | ||
|---|---|---|
In this paper, we study sparse representation of large-size natural scenes via local spatial dependency decomposition. We propose a local independent factorization model of natural scenes and develop a learning algorithm for adaptation of the synaptic weights. We investigate the dependency of neighboring location of the natural scene patches and derive learning algorithm to train the visual neural network. Some numerical experiments on natural scenes are performed to show the sparse representation of the visual sensory information. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11760023_66 | ISNN (2) |
Keywords | Field | DocType |
neighboring location,local independent factorization model,local spatial dependency decomposition,numerical experiment,natural scene,visual sensory information,visual neural network,natural scene patch,sparse representation,large-size natural scene,factor model,neural network,spatial dependence | Computer vision,Pattern recognition,Computer science,Sparse approximation,Visual sensory,Scene statistics,Factorization,Artificial intelligence,Artificial neural network,Spatial Dependency,Machine learning | Conference |
Volume | ISSN | ISBN |
3972 | 0302-9743 | 3-540-34437-3 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Libo Ma | 1 | 15 | 3.73 |
| Liqing Zhang | 2 | 2713 | 181.40 |
| Wenlu Yang | 3 | 28 | 7.81 |