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Author (up) Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud
Title Image Vegetation Index through a Cycle Generative Adversarial Network Type Conference Article
Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal
Volume Issue Pages 1014-1021
Keywords
Abstract This paper proposes a novel approach to estimate the

Normalized Difference Vegetation Index (NDVI) just from

an RGB image. The NDVI values are obtained by using

images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The

cycled GAN network is able to obtain a NIR image from

a given gray scale image. It is trained by using unpaired

set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are

obtained from the provided RGB images). Then, the NIR

image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous

approaches are also provided.
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Notes Approved no
Call Number gtsi @ user @ Serial 106
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