Name
Abstract | ||
|---|---|---|
In this paper, we proposed evolutionary filter and classifier ensemble. We designed the face recognition system that is consists of training module and testing module. The training module is evolution step, that process make filter and classifier combination. In testing step, we identified face recognition using knowledge from made training step. The filters are applied preprocessing step. Captured images are varying illuminant images so we proposed evolutionary preprocessing filter combinations and classifier ensemble for data context. The Proposed classifier selection for efficient object recognition based on evolutionary computation and data context knowledge called context based evolutionary system. In proposed method, we distinguish the data characteristics of input image and filter selects a classifier system accordingly using evolutionary algorithm. The proposed method is high more than single method. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/978-3-540-36668-3_77 | PRICAI |
Keywords | Field | DocType |
evolutionary computing,object recognition,pattern recognition,evolutionary algorithm,face recognition | Facial recognition system,Evolutionary algorithm,Pattern recognition,Computer science,Image processing,Evolutionary computation,Preprocessor,Artificial intelligence,Classifier (linguistics),Machine learning,Genetic algorithm,Cognitive neuroscience of visual object recognition | Conference |
Volume | ISSN | Citations |
4099 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mi Young Nam | 1 | 61 | 15.03 |
| In-Ja Jeon | 2 | 30 | 3.57 |
| Phill Kyu Rhee | 3 | 60 | 24.82 |