Mitigation Strategies to Improve Reproducibility of Poverty Estimations From Remote Sensing Images Using Deep Learning-Reference-Cited by-同舟云学术

Mitigation Strategies to Improve Reproducibility of Poverty Estimations From Remote Sensing Images Using Deep Learning

Published:2022-08 Issue:8 Volume:9 Page:
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth and Space Science

Author:

Machicao J.¹^ORCID,Ben Abbes A.²,Meneguzzi L.¹,Corrêa P. L. P.¹^ORCID,Specht A.³,David R.⁴,Subsol G.⁵,Vellenich D.¹,Devillers R.⁶,Stall S.⁷,Mouquet N.²⁸,Chaumont M.⁵⁸,Berti‐Equille L.⁶^ORCID,Mouillot D.⁹

Affiliation:

1. Escola Politécnica da Universidade de São Paulo (EPUSP) São Paulo Brazil

2. FRB‐CESAB Montpellier France

3. Terrestrial Ecosystem Research Network University of Queensland Brisbane QLD Australia

4. European Research Infrastructure on Highly Pathogenic Agents AISBL Brussel Belgium

5. Research‐Team ICAR LIRMM CNRS University of Montpellier Montpellier France

6. Espace‐Dev (IRD‐UM‐UG‐UR‐UA‐UNC) Montpellier France

7. American Geophysical Union Florida WA USA

8. University of Nîmes Nîmes France

9. MARBEC Univ Montpellier CNRS Ifremer IRD Montpellier France

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022EA002379

Reference46 articles.

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2. Ayush K. Uzkent B. Burke M. Lobell D. &Ermon S.(2020).Generating interpretable poverty maps using object detection in satellite images. InProceedings of the twenty‐nineth international joint conference on artificial intelligence.https://doi.org/10.24963/ijcai.2020/608

3. 1,500 scientists lift the lid on reproducibility

4. Computing environments for reproducibility: Capturing the “Whole Tale”

5. Using satellite imagery to understand and promote sustainable development

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