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

Research output: Contribution to journal › Conference article › peer-review

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.

Original language	English
Pages (from-to)	260-266
Number of pages	7
Journal	CEUR Workshop Proceedings
Volume	2534
Publication status	Published - 12 Jan 2020
Event	2019 All-Russian Conference "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2019 - Berdsk, Russian Federation Duration: 26 Aug 2019 → 30 Aug 2019

Keywords

Decision tree
Multispectral image
Recognition
Similarity of observations

OECD FOS+WOS

1.02 COMPUTER AND INFORMATION SCIENCES

Cite this

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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 = "2020",

month = jan,

day = "12",

language = "English",

volume = "2534",

pages = "260--266",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "CEUR-WS",

note = "2019 All-Russian Conference {"}Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes{"}, SDM 2019 ; Conference date: 26-08-2019 Through 30-08-2019",

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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 - 2020/1/12

Y1 - 2020/1/12

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

T2 - 2019 All-Russian Conference "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2019

Y2 - 26 August 2019 through 30 August 2019

ER -

Multi-spectral image recognition using solution trees based on similarity

Abstract

Keywords

OECD FOS+WOS

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