Interseasonal transfer learning for crop mapping using Sentinel-1 data

Interseasonal transfer learning for crop mapping using Sentinel-1 data

Crop maps are highly desired information in modern agriculture as they enable possessors to manage their business in the most optimal way. Usually in remote sensing, crop mapping is performed using satellite images and within-season ground truth samples that are collected in extensive survey campaig...

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Bibliographic Details
Main Authors:	Miloš Pandžić, Dejan Pavlović, Predrag Matavulj, Sanja Brdar, Oskar Marko, Vladimir Crnojević, Milan Kilibarda
Format:	Article
Language:	English
Published:	Elsevier 2024-04-01
Series:	International Journal of Applied Earth Observations and Geoinformation
Subjects:	Transfer learning Crop mapping Sentinel-1 Pre-trained model Domain
Online Access:	http://www.sciencedirect.com/science/article/pii/S1569843224000724

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