Use of shadows for extracting buildings in aerial images
Computer Vision, Graphics, and Image Processing
Spatial concepts, geometric data models, and geometric data structures
Computers & Geosciences - Special issue on GIS design models
Automatic Finding of Main Roads in Aerial Images by Using Geometric-Stochastic Models and Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional access methods
ACM Computing Surveys (CSUR)
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Machine Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Interpretation of Scanned Maps: Reconstruction of Contour Lines
GREC '97 Selected Papers from the Second International Workshop on Graphics Recognition, Algorithms and Systems
Interpretation of Geographic Vector-Data in Practice
GREC '99 Selected Papers from the Third International Workshop on Graphics Recognition, Recent Advances
Discovery of spatial association rules in geo-referenced census data: A relational mining approach
Intelligent Data Analysis
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Automating the interpretation of a map in order to locate some geographical objects and their relations is a challenging task, which goes beyond the transformation of map images into a vectorized representation and the recognition of symbols. In this work, we present an approach to the automated interpretation of vectorized topographic maps. It is based on the generation of logic descriptions of maps and the application of symbolic Machine Learning tools to these descriptions. This paper focuses on the definition of computational methods for the generation of logic descriptions of map cells and briefly describes the use of these logic descriptions in an inductive learning task.