A Texture Fuzzy Classifier Based on the Training Set Clustering by a Self-Organizing Neural Network; Communications in Computer and Information Science; Vol. 542 : Analysis of Images, Social Networks and Texts
| Parent link: | Communications in Computer and Information Science Vol. 542 : Analysis of Images, Social Networks and Texts.— 2015.— [P. 187-195] |
|---|---|
| Հիմնական հեղինակ: | |
| Համատեղ հեղինակ: | |
| Այլ հեղինակներ: | , |
| Ամփոփում: | Title screen The paper presents a fuzzy approach to the texture classification. According to the classifier the texture class is represented as a set of clusters in N-dimensional feature space that allows generating a cluster or clusters with an arbitrary shape and precisely reflecting any group of the vectors connected with the class. For each texture class it configures the self-organizing features map and estimates a degree of the overlap of the neighboring classes. Upon matching the maps each of them creates a set of fuzzy rules reflecting the feature value statistical distribution in its clusters. Advantages of the system are simplicity of the structure generation, functioning and performance. The suggested classification technique is universal and can be used not only as a texture analyzer but independently for many other real-world classification tasks. Режим доступа: по договору с организацией-держателем ресурса |
| Լեզու: | անգլերեն |
| Հրապարակվել է: |
2015
|
| Խորագրեր: | |
| Առցանց հասանելիություն: | http://dx.doi.org/10.1007/978-3-319-26123-2_18 |
| Ձևաչափ: | Էլեկտրոնային Գրքի գլուխ |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=647733 |
MARC
| LEADER | 00000naa0a2200000 4500 | ||
|---|---|---|---|
| 001 | 647733 | ||
| 005 | 20260825143841.0 | ||
| 035 | |a (RuTPU)RU\TPU\network\12885 | ||
| 090 | |a 647733 | ||
| 100 | |a 20160421d2015 k||y0rusy50 ba | ||
| 101 | 0 | |a eng | |
| 135 | |a drcn ---uucaa | ||
| 181 | 0 | |a i | |
| 182 | 0 | |a b | |
| 200 | 1 | |a A Texture Fuzzy Classifier Based on the Training Set Clustering by a Self-Organizing Neural Network |f S. V. Aksenov, K. A. Kostin, D. N. Laykom | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 21 tit.] | ||
| 330 | |a The paper presents a fuzzy approach to the texture classification. According to the classifier the texture class is represented as a set of clusters in N-dimensional feature space that allows generating a cluster or clusters with an arbitrary shape and precisely reflecting any group of the vectors connected with the class. For each texture class it configures the self-organizing features map and estimates a degree of the overlap of the neighboring classes. Upon matching the maps each of them creates a set of fuzzy rules reflecting the feature value statistical distribution in its clusters. Advantages of the system are simplicity of the structure generation, functioning and performance. The suggested classification technique is universal and can be used not only as a texture analyzer but independently for many other real-world classification tasks. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 461 | 1 | |t Communications in Computer and Information Science | |
| 463 | 1 | |t Vol. 542 : Analysis of Images, Social Networks and Texts |o 4th International Conference, AIST 2015, Yekaterinburg, Russia, April 9–11, 2015, Revised Selected Papers |o proceedings |v [P. 187-195] |d 2015 | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a самоорганизующиеся карты | |
| 700 | 1 | |a Aksenov |b S. V. |c Specialist in the field of informatics and computer technology |c Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences |f 1983- |g Sergey Vladimirovich |3 (RuTPU)RU\TPU\pers\31378 |9 15550 | |
| 701 | 1 | |a Kostin |b K. A. |c specialist in the field of Informatics and computer engineering |c engineer at Tomsk Polytechnic University |f 1992- |g Kirill Aleksandrovich |3 (RuTPU)RU\TPU\pers\36590 | |
| 701 | 1 | |a Laykom |b D. N. |c specialist in the field of informatics and computer technology |c Engineer of Tomsk Polytechnic University |f 1990- |g Dmitriy Nikolaevich |3 (RuTPU)RU\TPU\pers\33832 | |
| 712 | 0 | 2 | |a Томский политехнический университет |b Институт кибернетики, ИК |c 2010-2017 |9 27025 |
| 801 | 2 | |a RU |b 63413507 |c 20211015 |g RCR | |
| 850 | |a 63413507 | ||
| 856 | 4 | |u http://dx.doi.org/10.1007/978-3-319-26123-2_18 | |
| 942 | |c CF | ||