Name
Abstract | ||
|---|---|---|
For resolving a restoration problem of degraded and noisy image, we investigate the Hopfield neural network, and we employ the eliminating highest error EHE criterion in intention to improving performances of network. Moreover, with the purpose to make a better restoration, we take in consideration a human perception in restoration process. To do this, we introduce an adaptive regularization scheme, with contribution of a local statistical analysis, to assigning each pixel one regularization parameter regarding to its spatial activity. Due to various values of regularization parameter, this scheme permit us expanding the one network to a network of network NON, which we subsequently elucidate its analogy with the human visual system, a cortex. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/3-540-45723-2_27 | IWANN (2) |
Keywords | Field | DocType |
adaptive regularization scheme,hopfield neural network,neural networks,human perception,better restoration,image restoration,regularization parameter,restoration problem,network non,scheme permit,human visual system,restoration process,statistical analysis,neural network | Pattern recognition,Computer science,Human visual system model,Image processing,Regularization (mathematics),Pixel,Artificial intelligence,Analogy,Image restoration,Artificial neural network,Perception | Conference |
ISBN | Citations | PageRank |
3-540-42237-4 | 1 | 0.38 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Souheila Ghennam | 1 | 1 | 0.72 |
| Khier Benmahammed | 2 | 110 | 10.73 |