@inproceedings{MTMT:33079576,
	title = {The effect of different consequent setting on the effectiveness of Kóczy-Hirota fuzzy rule interpolation in colonoscopy image classification},
	url = {https://m2.mtmt.hu/api/publication/33079576},
	author = {ISMAIL, RANEEM and Sziová, Brigita and Taha, Hussein and Nagy, Szilvia},
	booktitle = {2022 57th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)},
	doi = {10.1109/ICEST55168.2022.9828693},
	unique-id = {33079576},
	abstract = {The effect of the refinement of the consequent categories in Kï¿czy-Hirota fuzzy rule interpolation is studied in the model system of colonoscopy image classification. The colonoscopy image segments are classified based on 99 antecedents, which are statistical parameters of the image segments. The number of consequents is increased from 2 - contains polyp, or does not contain polyp - to a more refined set distribution based on the polyp content of the image segment. © 2022 IEEE.},
	keywords = {Colonoscopy; Colonoscopy; endoscopy; interpolation; fuzzy rule interpolation; fuzzy rule interpolation; Image segmentation; statistical parameters; Fuzzy inference; Fuzzy rules; Image classification; Image classification; fuzzy classification; fuzzy classification; Modelling systems; Classifieds; Images classification; Image segments},
	year = {2022},
	pages = {123-126},
	orcid-numbers = {Nagy, Szilvia/0000-0001-9556-5095}
}

@article{MTMT:32253484,
	title = {On the Selection the Rule Membership Functions and Fuzzy Rule Interpolation},
	url = {https://m2.mtmt.hu/api/publication/32253484},
	author = {Nagy, Szilvia and Lilik, Ferenc and Sziová, Brigita and Szujó, Szonja and Kóczy, T. László},
	doi = {10.1007/978-3-030-74970-5_13},
	journal-iso = {STUD COMP INTELLIG},
	journal = {STUDIES IN COMPUTATIONAL INTELLIGENCE},
	volume = {959},
	unique-id = {32253484},
	issn = {1860-949X},
	year = {2022},
	eissn = {1860-9503},
	pages = {111-118},
	orcid-numbers = {Nagy, Szilvia/0000-0001-9556-5095; Kóczy, T. László/0000-0003-1316-4832}
}

@misc{MTMT:32947963,
	title = {Orvosi felvételek wavelet, fuzzy Hough-transzformáció, entrópia és Hesse-szűrő alapú elemzése},
	url = {https://m2.mtmt.hu/api/publication/32947963},
	author = {Sziová, Brigita},
	unique-id = {32947963},
	year = {2021}
}

@{MTMT:31872530,
	title = {On the Applicability of Fuzzy Rule Interpolation and Wavelet Analysis in Colorectal Image Segment Classification},
	url = {https://m2.mtmt.hu/api/publication/31872530},
	author = {Nagy, Szilvia and Lilik, Ferenc and Sziová, Brigita and Kovács, Melinda Ágnes and Kóczy, T. László},
	booktitle = {Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications},
	doi = {10.1007/978-3-030-54341-9_21},
	unique-id = {31872530},
	year = {2021},
	pages = {243-255},
	orcid-numbers = {Nagy, Szilvia/0000-0001-9556-5095; Kóczy, T. László/0000-0003-1316-4832}
}

@inproceedings{MTMT:32499799,
	title = {On classical and fuzzy Hough transform in colonoscopy image processing},
	url = {https://m2.mtmt.hu/api/publication/32499799},
	author = {Nagy, Szilvia and ISMAIL, RANEEM and Sziová, Brigita and Kóczy, T. László},
	booktitle = {2021 IEEE AFRICON Conference},
	doi = {10.1109/AFRICON51333.2021.9570897},
	unique-id = {32499799},
	abstract = {Hough transform is used to find lines on edge-filtered images that are given in parametric form. As the fuzzy extension of the Hough transform has been proven to be more robust in environments where the lines to be found by them are not strictly following the formula given by the parametric equation of the Hough transform due to noise and weak and blurred contours, in the following considerations, we study the applicability of the circular fuzzy Hough transform for analyzing colonoscopy pictures and detecting colorectal polyps.},
	year = {2021},
	orcid-numbers = {Nagy, Szilvia/0000-0001-9556-5095; Kóczy, T. László/0000-0003-1316-4832}
}

@article{MTMT:32112643,
	title = {Application of Structural Entropy and Spatial Filling Factor in Colonoscopy Image Classification},
	url = {https://m2.mtmt.hu/api/publication/32112643},
	author = {Sziová, Brigita and Nagy, Szilvia and Fazekas, Zoltán},
	doi = {10.3390/e23080936},
	journal-iso = {ENTROPY-SWITZ},
	journal = {ENTROPY},
	volume = {23},
	unique-id = {32112643},
	year = {2021},
	eissn = {1099-4300},
	orcid-numbers = {Nagy, Szilvia/0000-0001-9556-5095; Fazekas, Zoltán/0000-0001-5159-4476}
}

@inproceedings{MTMT:31925021,
	title = {The Effects of Preprocessing on Colorectal Polyp Detecting by Fuzzy Algorithm},
	url = {https://m2.mtmt.hu/api/publication/31925021},
	author = {Sziová, Brigita and Nagy, Szilvia and Kóczy, T. László},
	booktitle = {Recent Developments and the New Direction in Soft-Computing Foundations and Applications: Selected Papers from the 7th World Conference on Soft Computing},
	doi = {10.1007/978-3-030-47124-8_28},
	unique-id = {31925021},
	year = {2021},
	pages = {347-357},
	orcid-numbers = {Nagy, Szilvia/0000-0001-9556-5095; Kóczy, T. László/0000-0003-1316-4832}
}

@article{MTMT:31925018,
	title = {On wavelet based enhancing possibilities of fuzzy classification methods},
	url = {https://m2.mtmt.hu/api/publication/31925018},
	author = {Lilik, Ferenc and Solecki, Levente and Sziová, Brigita and Kóczy, T. László and Nagy, Szilvia},
	doi = {10.14313/JAMRIS/2-2020/18},
	journal-iso = {J AUTOMAT MOBIL ROBOT INTELL SYST},
	journal = {JOURNAL OF AUTOMATION MOBILE ROBOTICS AND INTELLIGENT SYSTEMS},
	volume = {14},
	unique-id = {31925018},
	issn = {1897-8649},
	year = {2020},
	eissn = {2080-2145},
	pages = {32-41},
	orcid-numbers = {Kóczy, T. László/0000-0003-1316-4832; Nagy, Szilvia/0000-0001-9556-5095}
}

@article{MTMT:30772988,
	title = {On Wavelet Based Enhancing Possibilities of Fuzzy Classification Methods},
	url = {https://m2.mtmt.hu/api/publication/30772988},
	author = {Lilik, Ferenc and Solecki, Levente and Sziová, Brigita and Kóczy, T. László and Nagy, Szilvia},
	doi = {10.1007/978-3-030-18058-4_5},
	journal-iso = {ADV INT SYST COMPUT},
	journal = {ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING},
	volume = {945},
	unique-id = {30772988},
	issn = {2194-5357},
	abstract = {If the antecedents of a fuzzy classification method are derived from pictures or measured data, it might have too many dimensions to handle. A classification scheme based on such data has to apply a careful selection or processing of the measured results: either a sampling, re-sampling is necessary or the usage of functions, transformations that reduce the long, high dimensional observed data vector or matrix into a single point or to a low number of points. Wavelet analysis can be useful in such cases in two ways.As the number of resulting points of the wavelet analysis is approximately half at each filters, a consecutive application of wavelet transform can compress the measurement data, thus reducing the dimensionality of the signal, i.e., the antecedent. An SHDSL telecommunication line evaluation is used to demonstrate this type of applicability, wavelets help in this case to overcome the problem of a one dimensional signal sampling.In the case of using statistical functions, like mean, variance, gradient, edge density, Shannon or Renyi entropies for the extraction of the information from a picture or a measured data set, and they don not produce enough information for performing the classification well enough, one or two consecutive steps of wavelet analysis and applying the same functions for the thus resulting data can extend the number of antecedents, and can distill such parameters that were invisible for these functions in the original data set. We give two examples, two fuzzy classification schemes to show the improvement caused by wavelet analysis: a measured surface of a combustion engine cylinder and a colonoscopy picture. In the case of the first example the wear degree is to be determine, in the case of the second one, the roundish polyp content of the picture. In the first case the applied statistical functions are Renyi entropy differences, the structural entropies, in the second case mean, standard deviation, Canny filtered edge density, gradients and the entropies.In all the examples stabilized KH rule interpolation was used to treat sparse rulebases.The preliminary version of this paper was presented at the 3rd Conference on Information Technology, Systems Research and Computational Physics, 2-5 July 2018, Cracow, Poland [1].},
	year = {2020},
	eissn = {2194-5365},
	pages = {56-73},
	orcid-numbers = {Kóczy, T. László/0000-0003-1316-4832; Nagy, Szilvia/0000-0001-9556-5095}
}

@article{MTMT:30675950,
	title = {Applying Fuzzy Hough Transform for Identifying Honed Microgeometrical Surfaces},
	url = {https://m2.mtmt.hu/api/publication/30675950},
	author = {Nagy, Szilvia and Solecki, Levente and Sziová, Brigita and Sarkadi-Nagy, Balázs and Kóczy, T. László},
	doi = {10.1007/978-3-030-16024-1_5},
	journal-iso = {STUD COMP INTELLIG},
	journal = {STUDIES IN COMPUTATIONAL INTELLIGENCE},
	volume = {819},
	unique-id = {30675950},
	issn = {1860-949X},
	abstract = {In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent measurements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface processing method resulting in pattern consisting of straight valleys crossing at various angles. Honing pattern is of great help to find a special location. The main goal of this article is to find a method that is able to give some characteristic points that can be used for fitting two measured surfaces together. Hough transform is used in finding straight lines in an image or map, thus it could be used for determining crossing points of the honed surface. However, classical Hough transform either finds way too many disturbing lines in the case of a typical honed surface or almost none, depending on the parameter selection. To solve this rapid changing in the number of the resulting lines, we introduced fuzzy Hough transform. If a fuzzified version of the weights of the individual points in the Hough transform is used, the inverse of the transform becomes clearer, resulting in a pattern more suitable for finding the same location on two measured versions of a surface.},
	year = {2020},
	eissn = {1860-9503},
	pages = {35-42},
	orcid-numbers = {Nagy, Szilvia/0000-0001-9556-5095; Kóczy, T. László/0000-0003-1316-4832}
}