The research on enhancing LA estimation accuracy across domains for small sample data based on data augmentation and data transfer integration optimization system

The research on enhancing LA estimation accuracy across domains for small sample data based on data augmentation and data transfer integration optimization system

Context: The efficient and precise monitoring of rice leaf area (LA) is essential for variety selection and agricultural management. At present, LA estimation models based on high-throughput phenotyping technologies primarily depend on homogenized large sample datasets. These models encounter genera...

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Bibliographic Details
Main Authors: Ai-Dong Wang, Rui-Jie Li, Xiang-Qian Feng, Zi-Qiu Li, Wei-Yuan Hong, Hua-Xing Wu, Dan-Ying Wang, Song Chen
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Smart Agricultural Technology
Subjects:
Small sample data
Leaf area estimation
Machine learning
Data augmentation
Transfer learning
Integrated optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525003806
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