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. © 2012 Springer Berlin Heidelberg.
CITATION STYLE
Lomenie, N., & Racoceanu, D. (2012). Ontology-enhanced vision system for new microscopy imaging challenges. In Advances in Intelligent and Soft Computing (Vol. 120, pp. 157–172). https://doi.org/10.1007/978-3-642-25547-2_10
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