Analogy-making as perception: a computer model
Analogy-making as perception: a computer model
Handbook of Granular Computing
Handbook of Granular Computing
Rough Granular Computing in Knowledge Discovery and Data Mining
Rough Granular Computing in Knowledge Discovery and Data Mining
Hierarchical Classifiers for Complex Spatio-temporal Concepts
Transactions on Rough Sets IX
Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab
Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab
Approximate Reasoning by Parts: An Introduction to Rough Mereology
Approximate Reasoning by Parts: An Introduction to Rough Mereology
Approximations of functions: toward rough granular calculus
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Approximate boolean reasoning: foundations and applications in data mining
Transactions on Rough Sets V
Nearness of Objects: Extension of Approximation Space Model
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
Tolerance Approximation Spaces
Fundamenta Informaticae
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The problem considered in this paper is how to describe and compare visual objects. The solution to this problem stems from a consideration of nearness relations in two different forms of Efremovič proximity spaces. In this paper, the visual objects are picture elements in digital images. In particular, this problem is solved in terms of the application of rough sets in proximity spaces. The basic approach is to consider the nearness of the upper and lower approximation of a set introduced by Z. Pawlak during the early 1980s as a foundation for rough sets. Two forms of nearness relations are considered, namely, a spatial EF-and a descriptive EF-relation. This leads to a study of the nearness of objects either spatially or descriptively in the approximation of a set. The nearness approximation space model developed in 2007 is refined and extended in this paper, leading to new forms of nearness approximation spaces. There is a natural transition from the two forms of nearness relations introduced in this article to the study of nearness granules.