MULTI-CLASS SEGMENTATION OF HETEROGENEOUS AREAS IN BIOMEDICAL AND ENVIRONMENTAL IMAGES BASED ON THE ASSESSMENT OF LOCAL EDGE DENSITY

Imaging techniques employed in biomedical and ecological applications typically require complex equipment and experimental approaches, including sophisticated multispectral cameras, as well as physical markup of samples, altogether limiting their broad availability. Accordingly, computerized methods...

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Vydané v:	International archives of the photogrammetry, remote sensing and spatial information sciences. Ročník XLVIII-2/W3-2023; s. 233 - 238
Hlavní autori:	Sinitca, A. M., Lyanova, A. I., Kaplun, D. I., Zelenikhin, P. V., Imaev, R. G., Gafurov, A. M., Usmanov, B. M., Tishin, D. V., Kayumov, A. R., Bogachev, M. I.
Médium:	Journal Article Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	Gottingen Copernicus GmbH 12.05.2023 Copernicus Publications
Predmet:	Adaptive algorithms Algorithms Archives & records Chlorophyll Deep learning Density Detection Edge detection Environmental science Image segmentation Imaging techniques Remote sensing Vegetation
ISSN:	2194-9034, 1682-1750, 2194-9034
On-line prístup:	Získať plný text
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