Name
Abstract | ||
|---|---|---|
An experimentally supported model of cortical background activity is used to investigate the role of such activity in neural gain control. The model demonstrates the feasibility of a scheme for contrast enhancement whereby the overall intensity of an input pattern adjusts the dynamic range of a neuron such that it remains sensitive to contrast over a wide range of overall intensities. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.neucom.2004.10.056 | Neurocomputing |
Keywords | Field | DocType |
dynamically adjustable contrast enhancement,input pattern,overall intensity,dynamic range,cortical background activity.,neural gain control,cortical background activity,wide range,gain,contrast enhancement,gain control | Computer vision,Dynamic range,Pattern recognition,Artificial intelligence,Automatic gain control,Mathematics | Journal |
Volume | ISSN | Citations |
65-66, | Neurocomputing | 1 |
PageRank | References | Authors |
0.44 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hamish Meffin | 1 | 102 | 14.94 |
| Anthony N. Burkitt | 2 | 487 | 46.71 |
| David B. Grayden | 3 | 254 | 29.89 |