Explainable Yield Prediction
Explainable Yield Prediction is a yield forecasting methodology that distinguishes itself by providing transparent and interpretable mechanisms to elucidate the causal factors and decision logic underlying predicted yield outcomes.
17
Publications
758
Citations
53
Authors
25
Institutions
Publications per year
2017–2026
11
Parents
17
Crop yield prediction integrating genotype and weather variables using deep learning
Johnathon M. Shook, Tryambak Gangopadhyay, Linjiang Wu et al. · PLoS ONE · 2021 · 210 citations · Full text
Tongxi Hu, Xuesong Zhang, Gil Bohrer et al. · Agricultural and Forest Meteorology · 2023 · 120 citations
1–5 of 17
53
2
h-index
2 publications · 32 citations
2
h-index
1
h-index
1
h-index
1
h-index
1–5 of 53
25
Iowa State University
Ames, United States
2 h-index
7 publications
1.4K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
1 h-index
2 publications
106 citations

Tampere University
Tampere, Finland
1 h-index
1 publications
19 citations
State Key Laboratory of Chemical Engineering
Hangzhou, China
1 h-index
4 publications
80 citations
The Ohio State University
Columbus, United States
1 h-index
6 publications
720 citations
Dalian University
Dalian, China
1 h-index
1 publications
20 citations
Samsung (South Korea)
Seoul, South Korea
1 h-index
1 publications
34 citations
University of Ulster
Coleraine, United Kingdom
1 h-index
1 publications
30 citations
1–8 of 25
2 publications · 88 citations
2
h-index
2 publications · 32 citations
2
h-index
1 publications · 17 citations
1
h-index
1 publications · 34 citations
1
h-index
1 publications · 20 citations
1
h-index
1–5