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New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Object Recognition Based on Comparative Similarity Assessment

Author : Juliusz L. Kulikowski

Published in: Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Publisher: Springer International Publishing

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Abstract

In the paper a concept of object recognition based on their similarity assessment in case of nonhomogenous qualitative and quantitative objects’ features is presented. Moreover, it is assumed that the features’ intensity values are not given directly but by their pairwise comparative assessment. This corresponds to an intuitive, on human experience-based assessment of the objects’ properties. The proposed object recognition method is based on reference sets divided into credibility layers, according to a relative logical model and conceptual classes of similarity. This concept is illustrated by an example of a conceptual class of “irregular” objects, the “irregularity” being intuitively assessed. The method is presented in the form of an algorithm.

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Metadata
Title
Object Recognition Based on Comparative Similarity Assessment
Author
Juliusz L. Kulikowski
Copyright Year
2016
Book
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Print ISBN: 978-3-319-26225-3

Electronic ISBN: 978-3-319-26227-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-26227-7_23

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