Cited by 3,473Remote-Sensing Image ClassificationRemote Sensing and Land UseRemote Sensing in Agriculture

Support vector machines in remote sensing: a review

Mountrakis, Giorgos, Im, Jungho, Ogole, Caesar·2011·ISPRS Journal of Photogrammetry and Remote Sensing

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Crossref · 10.1016/j.isprsjprs.2010.11.001

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150 of 150 references verified0 citation errors · 0 not checkable

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  • Decremental and incremental strategies have been applied to integrate relevant data samples for SVR training and ignore irrelevant parts.

    “In order to improve the stability and robustness of SVR with largescale training samples, decremental and incremental strategies [136,137] have been applied to integrate the relevant data sample for SVR training and ignore the irrelevant part.”

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Authors
Mountrakis, G., Im, J., & Ogole, C.
Affiliations
State University of New York (US)
Corresponding author
Mountrakis, Giorgos
Venue
ISPRS Journal of Photogrammetry and Remote Sensing
Publisher
Elsevier BV
Published
2011-05
Volume
66
Issue
3
Pages
247-259
ISSN
0924-2716 (ISSN-L)
OpenAlex
W2063907334
Cited by
3,473
References
150
Citations by year
2026: 264 · 2025: 298 · 2024: 240 · 2023: 272 · 2022: 320 · 2021: 311 · 2020: 315 · 2019: 305 · 2018: 249 · 2017: 224 · 2016: 188 · 2015: 155 · 2014: 149 · 2013: 95 · 2012: 65
FWCI
149.00
Type
journal article
Language
en
Open access
closed
Locations
  • ISPRS Journal of Photogrammetry and Remote Sensing (publishedVersion)
  • Scholarworks@UNIST (Ulsan National Institute of Science and Technology) (submittedVersion)
Topics
  • Physical Sciences › Engineering › Media Technology › Remote-Sensing Image Classification
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Remote Sensing and Land Use
  • Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
Keywords
support vector machine, remote sensing image analysis, airborne imagery, satellite imagery, small training sample size, parameter selection, generalization, classification

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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