Knowledge-based assistant for colonscopy
IEA/AIE '90 Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2
Improving the landcover classification using domain knowledge
AI Communications
Knowledge modeling for the image understanding task as a design task
Expert Systems with Applications: An International Journal
An open source object-based framework to extract landform classes
Expert Systems with Applications: An International Journal
Distance images and intermediate-level vision
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Real-time landing place assessment in man-made environments
Machine Vision and Applications
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In this paper, we describe the organization of a rule-based system, SPAM, that uses map and domain-specific knowledge to interpret airport scenes. This research investigates the use of a rule-based system for the control of image processing and interpretation of results with respect to a world model, as well as the representation of the world model within an image/map database. We present results on the interpretation of a high-resolution airport scene wvhere the image segmentation has been performed by a human, and by a region-based image segmentation program. The results of the system's analysis is characterized by the labeling of individual regions in the image and the collection of these regions into consistent interpretations of the major components of an airport model. These interpretations are ranked on the basis of their overall spatial and structural consistency. Some evaluations based on the results from three evolutionary versions of SPAM are presented.