Применение кластеризации k-means и анализа гистограмм для автоматизации предварительной обработки изображений дискомицетов, полученных в среде обитания

Standard

Применение кластеризации k-means и анализа гистограмм для автоматизации предварительной обработки изображений дискомицетов, полученных в среде обитания. / Filimonova, D. A.; Vorob'eva, Irina G.; Filimonov, Alexander Yu.
в: Вестник Томского государственного университета. Биология, Том 2023, № 63, 2023, стр. 111 - 117.

Результаты исследований: Вклад в журнал › Статья › Рецензирование

BibTeX

@article{42937c2cc1f94b9c95f514b65414c185,

title = "Применение кластеризации k-means и анализа гистограмм для автоматизации предварительной обработки изображений дискомицетов, полученных в среде обитания",

abstract = "The study of biological diversity requires a thorough inventory of all groups of organisms, including destructors, among which fungi play a significant role. Discomycetes, a group of orders of fungi of the Ascomycota phylum, require close attention from researchers due to their low level of knowledge. The paper proposes an approach to automating the process of inventory of representatives of this group of orders and presents a prototype of a software package that allows one to identify the presence of fruit bodies of discomycetes in photographs taken in the natural habitat. A feature of the proposed solution is the application of the k-means clustering method, the use of scaled histograms to determine the presence of an image of the fruit body of Discomycetes in this image, and the prospects for using this tool in machine learning are described using neural networks.",

author = "Filimonova, {D. A.} and Vorob'eva, {Irina G.} and Filimonov, {Alexander Yu.}",

year = "2023",

doi = "10.17223/19988605/63/13",

language = "Русский",

volume = "2023",

pages = "111 -- 117",

journal = "Вестник Томского государственного университета. Биология",

issn = "1998-8591",

publisher = "Национальный исследовательский Томский государственный университет",

number = "63",

}

RIS

TY - JOUR

T1 - Применение кластеризации k-means и анализа гистограмм для автоматизации предварительной обработки изображений дискомицетов, полученных в среде обитания

AU - Filimonova, D. A.

AU - Vorob'eva, Irina G.

AU - Filimonov, Alexander Yu.

PY - 2023

Y1 - 2023

N2 - The study of biological diversity requires a thorough inventory of all groups of organisms, including destructors, among which fungi play a significant role. Discomycetes, a group of orders of fungi of the Ascomycota phylum, require close attention from researchers due to their low level of knowledge. The paper proposes an approach to automating the process of inventory of representatives of this group of orders and presents a prototype of a software package that allows one to identify the presence of fruit bodies of discomycetes in photographs taken in the natural habitat. A feature of the proposed solution is the application of the k-means clustering method, the use of scaled histograms to determine the presence of an image of the fruit body of Discomycetes in this image, and the prospects for using this tool in machine learning are described using neural networks.

AB - The study of biological diversity requires a thorough inventory of all groups of organisms, including destructors, among which fungi play a significant role. Discomycetes, a group of orders of fungi of the Ascomycota phylum, require close attention from researchers due to their low level of knowledge. The paper proposes an approach to automating the process of inventory of representatives of this group of orders and presents a prototype of a software package that allows one to identify the presence of fruit bodies of discomycetes in photographs taken in the natural habitat. A feature of the proposed solution is the application of the k-means clustering method, the use of scaled histograms to determine the presence of an image of the fruit body of Discomycetes in this image, and the prospects for using this tool in machine learning are described using neural networks.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85189243249

U2 - 10.17223/19988605/63/13

DO - 10.17223/19988605/63/13

M3 - Статья

VL - 2023

SP - 111

EP - 117

JO - Вестник Томского государственного университета. Биология

JF - Вестник Томского государственного университета. Биология

SN - 1998-8591

IS - 63

ER -

ID: 55350766