Ontology-enhanced vision system for new microscopy imaging challenges

Nicolas Lomenie, Daniel Racoceanu

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


Artificial intelligence and computer vision have long been separate fields basically because the data structures to work with and to reason about were rather distinct and non permeable. Ontology-driven systems may have the ability to build a bridge between these two fundamental topics involved in intelligent system design. We provide preliminary insights about this powerful synergy in the field of digitized pathology as a brand new topic in which, like currently for satellite imaging, the amount of raw data and high-level concepts to handle give no other choice but to innovate about the low-level image image processing machine and the knowledge modeling framework integration. Above all, the end-user who is most of the time naive about signal, image and algorithmic issues can thence play the key role in the design of such enhanced vision system.

Idioma originalInglés
Título de la publicación alojadaAdvances in Bio-Imaging
Subtítulo de la publicación alojadaFrom Physics to Signal Understanding Issues: State-of-the-Art and Challenges
EditoresNicolas Lomenie, Daniel Racoceanu, Alexandre Gouaillard
Número de páginas16
EstadoPublicada - 2012
Publicado de forma externa

Serie de la publicación

NombreAdvances in Intelligent and Soft Computing
ISSN (versión impresa)1867-5662


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