Sensor Fusion for Weeding is a computational framework that integrates multisensory data from heterogeneous sources, such as optical, spectral, and spatial sensors, to enhance the accuracy and robustness of weed detection and discrimination in agricultural robotics by leveraging complementary information while mitigating individual sensor limitations.
4
Publications
175
Citations
13
Authors
4
Institutions
Publications per year
2017–2026
2
Parents
Publications
4
A robot platform for unmanned weeding in a paddy field using sensor fusion
Gook-Hwan Kim, Sang‐Cheol Kim, Youngki Hong et al. · 2012 · 19 citations
1–5 of 4
Authors
13
- BL
2
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- JG
2
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- LT
2
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- YH
1
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- MZ
1
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1–5 of 13
Institutions
4
National Academy of Agricultural Science
Wanju, South Korea
1 h-index
4 publications
76 citations
Iowa State University
Ames, United States
1 h-index
3 publications
330 citations
Guangxi University
Nanning, China
1 h-index
5 publications
145 citations
Kyung Hee University
Seoul, South Korea
1 h-index
1 publications
19 citations
Skolkovo Institute of Science and Technology
Skolkovo, Russia
1 publications
17 citations
Saint Petersburg State University of Aerospace and Instrumentation
Saint Petersburg, Russia
1 publications
17 citations
Rakuten (Japan)
Tokyo, Japan
1 publications
17 citations
1–7 of 4
Venues
- Journal of Field Robotics
JFR · 1 publications · 110 citations
1
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- Frontiers in Plant Science
1 publications · 29 citations
1
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- 2015 ASABE International Meeting
Conference · 1 publications · 17 citations
1
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- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
1 publications · 17 citations
1–4