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Physics-guided deep learning for crop yield estimation

delete2025-09-15
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PRE
AI
B
Bowen Cao
L
Le Yu *
L
Liheng Zhong
S
Shengchao Qiao
S
Shen Tan
X
Xiaomeng Huang
H
Han Wang
DOI:10.1016/j.eja.2025.127850delete
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Abstract

Abstract

En 中文
• A physics-guided deep learning model for crop yield estimation is proposed. • The physics-guided deep learning model outperforms the conventional models. • The proposed model shows better universality and spatiotemporal extrapolation. • The structurally hybrid modeling tackles challenges of large-scale yield estimation.

Journal

European Journal of Agronomy cover
European Journal of Agronomy
IF:
5.5
Papers:
625
Citations:
1.3W

Organization

T
tsinghua university
Scholars:
11.8W
Papers: 10.0W
Citations: 137
P
peking university
Scholars:
11.8W
Papers: 8.7W
Citations: 146
H
Hainan University
Scholars:
2.0W
Papers: 1.2W
Citations: 1.9W
A
ant group
Scholars:
235
Papers: 117
Citations: 0
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