Land Cover Mapping From Multiple Complementary Experts Under Heavy Class Imbalance-Reference-Cited by-同舟云学术

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Land Cover Mapping From Multiple Complementary Experts Under Heavy Class Imbalance

Published:2024 Issue: Volume:17 Page:6468-6477
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Zermatten Valerie¹^ORCID,Lu Xiaolong²^ORCID,Castillo-Navarro Javiera¹^ORCID,Kellenberger Tobias³^ORCID,Tuia Devis¹^ORCID

Affiliation:

1. Laboratory for Environmental Computational Science and Earth Observation, Ecole Polytechnique Federale de Lausanne, Sion, Switzerland

2. Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland

3. Federal Office of Topography swisstopo, Bern, Switzerland

Funder

Federal Office of Topography swisstopo

Gold Open Access fund of the EPFL library

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10444917.pdf?arnumber=10444917

Reference48 articles.

1. Deep Learning‐based Semantic Segmentation in Remote Sensing

2. Artificial intelligence to advance earth observation: A perspective;Tuia,2023

3. Land cover mapping at very high resolution with rotation equivariant CNNs: Towards small yet accurate models

4. European Landscape Dynamics

5. Fast animal detection in UAV images using convolutional neural networks

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