Pixel-level Yield Estimation
Pixel-Level Yield Estimation is a remote sensing method that quantifies crop yield at the individual image pixel scale by leveraging spectral, spatial, and temporal data to model productivity variations within agricultural fields.
154
Publications
10.3K
Citations
714
Authors
286
Institutions
Publications per year
2017–2026
98
154
Detection and analysis of wheat spikes using Convolutional Neural Networks
Md. Mehedi Hasan, Joshua Chopin, Hamid Laga et al. · Plant Methods · 2018 · 278 citations · Full text
Agriculture, Agronomy, Crop Sciences +17
Jianxi Huang, Hongyuan Ma, Fernando Sedano et al. · European Journal of Agronomy · 2018 · 251 citations · Full text
1–5 of 154
714
National Engineering Research Center for Information Technology in Agriculture, China
3 publications · 228 citations
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3
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3
h-index
3
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3
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1–5 of 714
286

Chinese Academy of Sciences
Beijing, China
12 h-index
26 publications
1.4K citations
China Agricultural University
Beijing, China
8 h-index
38 publications
3.9K citations
University of Chinese Academy of Sciences
Beijing, China
7 h-index
11 publications
497 citations
Ministry of Agriculture and Rural Affairs
Beijing, China
6 h-index
28 publications
1.2K citations
Institute of Remote Sensing and Digital Earth
Beijing, China
6 h-index
6 publications
520 citations
Chinese Academy of Agricultural Sciences
Beijing, China
6 h-index
25 publications
2.1K citations
University of Nebraska–Lincoln
Lincoln, United States
5 h-index
10 publications
465 citations
Institute of Agricultural Resources and Regional Planning
Beijing, China
5 h-index
20 publications
1.8K citations
1–8 of 286
21 publications · 1.5K citations
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JAG · 9 publications · 1K citations
9
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9 publications · 1K citations
9
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8 publications · 1.1K citations
8
h-index
9 publications · 766 citations
8
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1–5