Pattern recognition: human and mechanical
Pattern recognition: human and mechanical
Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Fundamentals of pattern recognition (2nd revised and expanded ed.)
Fundamentals of pattern recognition (2nd revised and expanded ed.)
Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Neuro-Dynamic Programming
Rough-Neuro-Computing: Techniques for Computing with Words
Rough-Neuro-Computing: Techniques for Computing with Words
Rough Sets: Mathematical Foundations
Rough Sets: Mathematical Foundations
Data Mining
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Reinforcement Learning with Approximation Spaces
Fundamenta Informaticae
Near Sets. Special Theory about Nearness of Objects
Fundamenta Informaticae - New Frontiers in Scientific Discovery - Commemorating the Life and Work of Zdzislaw Pawlak
Approximation spaces in off-policy Monte Carlo learning
Engineering Applications of Artificial Intelligence
Approximation spaces and information granulation
Transactions on Rough Sets III
Matching 2d image segments with genetic algorithms and approximation spaces
Transactions on Rough Sets V
Nearness of Objects: Extension of Approximation Space Model
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
Toward Approximate Adaptive Learning
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Rough sets and near sets in medical imaging: a review
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
Feature selection: near set approach
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
A generalization of near set model
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Nearness approximation space based on axiomatic fuzzy sets
International Journal of Approximate Reasoning
Nearness of Objects: Extension of Approximation Space Model
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
Development of Near Sets Within the Framework of Axiomatic Fuzzy Sets
Fundamenta Informaticae
| Hi-index | 0.01 |
The problem considered in this paper is how to recognize objects that are qualitatively but not necessarily spatially near each other. The term qualitatively near is used here to mean closeness of descriptions or distinctive characteristics of objects. The solution to this problem is inspired by the work of Zdzisław Pawlak during the early 1980s on the classification of objects by means of their attributes. In working toward a solution of the problem of the approximation of sets that are qualitatively near each other, this article considers an extension of the basic model for approximation spaces. The basic approach to object recognition is to consider the degree of overlap between families of perceptual neighbourhoods and a set of objects representing a standard. The proposed approach to object recognition includes a refinement of the generalized model for approximation spaces. This is a natural extension of recent work on nearness of objects. A byproduct of the proposed object recognition method is what we call a near set. The contribution of this article is an approximation space-based approach to object recognition formulated in the context of near sets.