Rice disease and pest identification integrating albert pre-trained language model and improved BILSTM

Rice disease and pest identification integrating albert pre-trained language model and improved BILSTM

ABSTRACT To solve the low recognition accuracy and slow recognition efficiency in traditional rice disease and pest recognition technology, this study adopts a bidirectional encoder representation pre-training model from a transformer for preliminary recognition of rice diseases and pests. At the sa...

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Bibliographic Details
Main Authors: Zhigui Dong, Tianyi Yang, Yanchao Wang
Format: Article
Language:English
Published: Universidade Federal do Ceará 2025-05-01
Series:Revista Ciência Agronômica
Subjects:
Rice
Diseases and pests
Pre-trained model
Bi-LSTM
Recognition
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902025000100664&lng=en&tlng=en
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