DEEP LEARNING FOR REMOTE SENSING IMAGE CLASSIFICATION FOR AGRICULTURE APPLICATIONS
This research examines the ability of deep learning methods for remote sensing image classification for agriculture applications. U-net and convolutional neural networks are fine-tuned, utilized and tested for crop/weed classification. The dataset for this study includes 60 top-down images of an org...
Main Authors: | L. Hashemi-Beni, A. Gebrehiwot |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2020-11-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIV-M-2-2020/51/2020/isprs-archives-XLIV-M-2-2020-51-2020.pdf |
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