SEMANTIC SEGMENTATION IN MULTISPECTRAL IMAGERY
DOI:
https://doi.org/10.53920/ITS-2024-1-2Keywords:
image processing, multispectral images, convolutional neural networks, CNN, U-Net-like architecture, Normalized Difference Vegetation Index, NDVIAbstract
A U-Net-type convolutional neural network proposed for semantic segmentation in multispectral imagery. The architecture of this network has modified and expanded to achieve better results with a smaller training dataset.
A comparison conducted between the results of vegetation zone delineation in multispectral images using a convolutional neural network with a modified U-Net-like architecture and the Normalized Difference Vegetation Index.
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Published
2024-06-30
How to Cite
BUTKO І. М., GOLUBENKO О. І., & МАКОВЕЙЧУК, О. М. (2024). SEMANTIC SEGMENTATION IN MULTISPECTRAL IMAGERY. ITSynergy, (1), 16–29. https://doi.org/10.53920/ITS-2024-1-2
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