SEMANTIC SEGMENTATION IN MULTISPECTRAL IMAGERY

Authors

DOI:

https://doi.org/10.53920/ITS-2024-1-2

Keywords:

image processing, multispectral images, convolutional neural networks, CNN, U-Net-like architecture, Normalized Difference Vegetation Index, NDVI

Abstract

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.

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

Issue

Section

Presentation