Name
Abstract | ||
|---|---|---|
In this work an approach to an adaptive vision system is presented. It is based on a homeostatic approach where the system state is represented as a set of artificial hormones which are affected by the environmental changes. To compensate these changes, the vision system is endowed with drives which are in charge of modifying the system parameters in order to keep the system performance as high as possible. To coordinate the drives in the system, a supervisor level based on fuzzy logic has been added. Experiments in both controlled and uncontrolled environments have been carried out to validate the proposal. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11492429_23 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
fuzzy logic,system state,environmental change,system parameter,supervisor level,system performance,artificial hormone,vision system,homeostatic approach,adaptive vision system,pattern recognition,computer vision,image processing,empirical method,systems theory,adaptive system,image analysis | Supervisor,Systems theory,Machine vision,Adaptive system,Computer science,Fuzzy logic,Image processing,Control engineering,Color balance,Artificial intelligence,Mobile robot,Distributed computing | Conference |
Volume | ISSN | ISBN |
3522 | 0302-9743 | 3-540-26153-2 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Javier Lorenzo-Navarro | 1 | 166 | 21.55 |
| Daniel Hernández | 2 | 0 | 0.34 |
| Cayetano Guerra | 3 | 96 | 5.45 |
| José Isern-González | 4 | 20 | 3.95 |