Optimizing dataset diversity for a robust deep-learning model in rice blast disease identification to enhance crop health assessment across diverse conditions

Magnaporthe oryzae, the pathogen that causes rice blast disease, poses a significant global threat to rice production. This disease may lead to yield losses exceeding 30 % in susceptible rice varieties. There is an urgent need for more effective detection solutions, as traditional methods—primarily...

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Bibliographic Details
Main Authors: Reuben Alfred, Judith Leo, Shubi Felix Kaijage
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Smart Agricultural Technology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375524003307
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