Browse State-of-the-Art › Crop Yield Prediction
Crop Yield Prediction
19 papers with code · 2 benchmarks · 3 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| 2018 Syngenta (2016 val) (1 row) | Transformer | Crop Yield Prediction Using Deep Neural Networks | code | — | Compare |
| SICKLE (1 row) | U-TAE | SICKLE: A Multi-Sensor Satellite Imagery Dataset Annotated with... | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
3 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
19 shown of 19 papers with code (48 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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20 Nov 2019 4 repositories listedCrop yield prediction is extremely challenging due to its dependence on multiple factors such as crop genotype, environmental factors, management practices, and their interactions.
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11 Mar 2018 3 repositories listedIn classifier (or regression) fusion the aim is to combine the outputs of several algorithms to boost overall performance.
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6 Jan 2023 2 repositories listedPrecision Agriculture and especially the application of automated weed intervention represents an increasingly essential research area, as sustainability and efficiency considerations are becoming more and more relevant.
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16 Apr 2021 2 repositories listedWe frame Earth surface forecasting as the task of predicting satellite imagery conditioned on future weather.
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2 May 2025 1 repository listedRemote sensing enables a wide range of critical applications such as land cover and land use mapping, crop yield prediction, and environmental monitoring.
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31 Mar 2024 1 repository listedAccurate and precise crop yield prediction is invaluable for decision making at both farm levels and regional levels.
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22 Jan 2024 1 repository listedThe GU module learned different weights based on the country and crop-type, aligning with the variable significance of each data source to the prediction task.
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Corn Yield Prediction Model with Deep Neural Networks for Smallholder Farmer Decision Support System8 Jan 2024 1 repository listedGiven the nonlinearity of the interaction between weather and soil variables, a deep neural network regressor (DNNR) is carefully designed with consideration to the depth, number of neurons of the hidden layers, and the…
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6 Dec 2023 1 repository listed Syntology ran 1 of 6 samples · 5 unverifiedOur method outperforms previous state-of-the-art methods for satellite image generation and is the first large-scale generative foundation model for satellite imagery.
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4 Dec 2023 1 repository listedFrom the 1980s to the 1990s, field data were gathered across the southern cotton belt of the United States.
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29 Nov 2023 1 repository listedOut of the 2, 370 samples, 351 paddy samples from 145 plots are annotated with multiple crop parameters; such as the variety of paddy, its growing season and productivity in terms of per-acre yields.
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16 Sep 2023 1 repository listed Syntology ran 5 of 6 samples · 1 unverified · 6 pointer-only (licence)In this work, we develop a deep learning-based solution, namely Multi-Modal Spatial-Temporal Vision Transformer (MMST-ViT), for predicting crop yields at the county level across the United States, by considering the…
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8 Apr 2023 1 repository listedWe propose to use counterfactual explanations (CFEs) for the identification of the features with the highest relevance on the shape of response curves generated by neural network black boxes.
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17 Nov 2021 1 repository listedAs far as we know, this is the first machine learning method that embeds geographical knowledge in crop yield prediction and predicts the crop yields at county level nationwide.
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20 Oct 2021 1 repository listedWe show that the performer-based models significantly outperform the traditional approaches, achieving an R score of 0.
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16 Jun 2021 1 repository listedWe present a fully automated model for in-season crop yield prediction, designed to work where there is a dearth of sub-national "ground truth" information.
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11 Dec 2020 1 repository listedHere, we define high-resolution Earth surface forecasting as video prediction of satellite imagery conditional on mesoscale weather forecasts.
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7 Feb 2019 1 repository listedCrop yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions.
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12 Feb 2017 1 repository listedAgricultural monitoring, especially in developing countries, can help prevent famine and support humanitarian efforts.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections