Combining the Pre-Trained Model Roberta with a Two-Layer Bidirectional Long- and Short-Term Memory Network and a Multi-Head Attention Mechanism for a Rice Phenomics Entity Classification Study

Combining the Pre-Trained Model Roberta with a Two-Layer Bidirectional Long- and Short-Term Memory Network and a Multi-Head Attention Mechanism for a Rice Phenomics Entity Classification Study

At a time when global food security is challenged, the importance of phenomics research on rice, as a major food crop, has become more and more prominent. In-depth analysis of rice phenotypic characteristics is of key importance to promote the genetic improvement of rice and sustainable agricultural...

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Bibliographic Details
Main Authors: Dayu Xu, Xinyu Zhu, Xuyao Zhang, Fang Xia
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:AgriEngineering
Subjects:
rice phenomics
deep learning models
Roberta
BiLSTM
entity classification
Online Access:https://www.mdpi.com/2624-7402/7/4/94
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