Multi-spectral image recognition using solution trees based on similarity

Vladimir B. Berikov; Igor A. Pestunov; Roman M. Kozinets; Sergey A. Rylov

Multi-spectral image recognition using solution trees based on similarity

Vladimir B. Berikov, Igor A. Pestunov, Roman M. Kozinets, Sergey A. Rylov

Результат исследования: Научные публикации в периодических изданиях › статья по материалам конференции

Аннотация

A method for constructing decision trees based on the mutual similarity of objects is proposed. The method allows obtaining complex decision boundaries, which have a clear logical interpretation. The results of the experiments confirm the effectiveness of the method for multispectral image recognition.

Язык оригинала	английский
Страницы (с-по)	260-266
Число страниц	7
Журнал	CEUR Workshop Proceedings
Том	2534
Состояние	Опубликовано - 1 янв 2019
Событие	2019 All-Russian Conference "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2019 - Berdsk, Российская Федерация Продолжительность: 26 авг 2019 → 30 авг 2019

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Berikov, V. B., Pestunov, I. A., Kozinets, R. M., & Rylov, S. A. (2019). Multi-spectral image recognition using solution trees based on similarity. CEUR Workshop Proceedings, 2534, 260-266.

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title = "Multi-spectral image recognition using solution trees based on similarity",

abstract = "A method for constructing decision trees based on the mutual similarity of objects is proposed. The method allows obtaining complex decision boundaries, which have a clear logical interpretation. The results of the experiments confirm the effectiveness of the method for multispectral image recognition.",

keywords = "Decision tree, Multispectral image, Recognition, Similarity of observations",

author = "Berikov, {Vladimir B.} and Pestunov, {Igor A.} and Kozinets, {Roman M.} and Rylov, {Sergey A.}",

year = "2019",

month = "1",

day = "1",

language = "English",

volume = "2534",

pages = "260--266",

journal = "CEUR Workshop Proceedings",

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Multi-spectral image recognition using solution trees based on similarity. / Berikov, Vladimir B.; Pestunov, Igor A.; Kozinets, Roman M.; Rylov, Sergey A.

В: CEUR Workshop Proceedings, Том 2534, 01.01.2019, стр. 260-266.

Результат исследования: Научные публикации в периодических изданиях › статья по материалам конференции

TY - JOUR

T1 - Multi-spectral image recognition using solution trees based on similarity

AU - Berikov, Vladimir B.

AU - Pestunov, Igor A.

AU - Kozinets, Roman M.

AU - Rylov, Sergey A.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - A method for constructing decision trees based on the mutual similarity of objects is proposed. The method allows obtaining complex decision boundaries, which have a clear logical interpretation. The results of the experiments confirm the effectiveness of the method for multispectral image recognition.

AB - A method for constructing decision trees based on the mutual similarity of objects is proposed. The method allows obtaining complex decision boundaries, which have a clear logical interpretation. The results of the experiments confirm the effectiveness of the method for multispectral image recognition.

KW - Decision tree

KW - Multispectral image

KW - Recognition

KW - Similarity of observations

UR - http://www.scopus.com/inward/record.url?scp=85078521757&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85078521757

VL - 2534

SP - 260

EP - 266

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

ER -

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