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Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review
M. Sheykhmousa,
M. Mahdianpari,
H. Ghanbari,
F. Mohammadimanesh,
Pedram Ghamisi,
Saeid Homayouni
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8 |
2020 |
8
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π
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African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning
24 auth.
T. Hengl,
Matthew Miller,
J. Krizan,
K. Shepherd,
Andrew Sila,
M. Kilibarda,
Ognjen AntonijeviΔ,
Luka GluΕ‘ica,
A. Dobermann,
S. Haefele,
...
S. McGrath,
Gifty E. Acquah,
J. Collinson,
L. Parente,
M. Sheykhmousa,
K. Saito,
Jean-Martial Johnson,
J. Chamberlin,
F. Silatsa,
M. Yemefack,
J. Wendt,
R. MacMillan,
Ichsani Wheeler,
J. Crouch
|
7 |
2020 |
7
π
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Post-Disaster Recovery Assessment with Machine Learning-Derived Land Cover and Land Use Information
M. Sheykhmousa,
N. Kerle,
M. Kuffer,
S. Ghaffarian
|
5 |
2019 |
5
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Peer Review #3 of "Variance of vegetation coverage and its sensitivity to climatic factors in the Irtysh River basin (v0.1)"
M. Sheykhmousa
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0 |
2021 |
0
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Peer Review #3 of "Variance of vegetation coverage and its sensitivity to climatic factors in the Irtysh River basin (v0.2)"
M. Sheykhmousa
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0 |
2021 |
0
π¦
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π¦
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UNDERSTANDING POST DISASTER RECOVERY THROUGH ASSESSMENT OF LAND COVER AND LAND USE CHANGES USING REMOTE SENSING
M. Sheykhmousa
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0 |
2018 |
0
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