Genetic Programming for High-Level Feature Learning in Crop Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Lu:2022:RemoteSensing,
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author = "Miao Lu and Ying Bi and Bing Xue and Qiong Hu and
Mengjie Zhang and Yanbing Wei and Peng Yang and
Wenbin Wu",
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title = "Genetic Programming for High-Level Feature Learning in
Crop Classification",
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journal = "Remote Sensing",
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year = "2022",
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volume = "14",
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number = "16",
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pages = "3982",
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month = aug,
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note = "Special Issue Remote Sensing for Mapping Farmland and
Agricultural Infrastructure",
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keywords = "genetic algorithms, genetic programming, crop
classification, feature learning, high-level features,
genetic programming representation",
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publisher = "MDPI AG",
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ISSN = "2072-4292",
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DOI = "doi:10.3390/rs14163982",
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size = "18 page",
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abstract = "Information on crop spatial distribution is essential
for agricultural monitoring and food security.
Classification with remote-sensing time series images
is an effective way to obtain crop distribution maps
across time and space. Optimal features are the
precondition for crop classification and are critical
to the accuracy of crop maps. Although several
approaches are available for extracting spectral,
temporal, and phenological features for crop
identification, these methods depend heavily on domain
knowledge and human experiences, adding uncertainty to
the final crop classification. This study proposed a
novel Genetic Programming (GP) approach to learning
high-level features from time series images for crop
classification to address this issue. We developed a
new representation of GP to extend the GP tree’s
width and depth to dynamically generate either fixed or
flexible informative features without requiring domain
knowledge. This new GP approach was wrapped with four
classifiers,",
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notes = "Key Laboratory of Agricultural Remote Sensing,
Ministry of Agriculture and Rural Affairs/Institute of
Agricultural Resources and Regional Planning, Chinese
Academy of Agricultural Sciences, Beijing 100081,
China",
- }
Genetic Programming entries for
Miao Lu
Ying Bi
Bing Xue
Qiong Hu
Mengjie Zhang
Yanbing Wei
Peng Yang
Wenbin Wu
Citations