Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42874
Título: A proposal for a homeostasis based adaptive vision system
Autores/as: Lorenzo-Navarro, Javier 
Hernández, Daniel 
Guerra, Cayetano
Isern-González, José 
Clasificación UNESCO: 120304 Inteligencia artificial
Fecha de publicación: 2005
Proyectos: Aprendizaje Interactivo de Mapas Multisensoriales en Robótica Móvil. 
Publicación seriada: Lecture Notes in Computer Science 
Conferencia: 2nd Iberian Conference on Pattern Recognition and Image Analysis 
Second Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005 
Resumen: 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.
URI: http://hdl.handle.net/10553/42874
ISBN: 978-3-540-26153-7
ISSN: 0302-9743
DOI: 10.1007/11492429_23
Fuente: Marques J.S., Pérez de la Blanca N., Pina P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3522. Springer, Berlin, Heidelberg
Colección:Actas de congresos
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