Identification of maize diseases based on dynamic convolution and tri-attention mechanism

Accurate, non-destructive classification of maize diseases is crucial for efficiently managing agricultural losses. While existing methods perform well in controlled environment dataset like PlantVillage, their accuracy often declines in real-world scenarios. In this work, ResNet50 is enhanced by in...

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Bibliographic Details

Main Authors:	Feilong tang, Rosalyn R. Porle, Hoe Tung Yew, Farrah Wong Hock Tze
Format:	Article
Language:	en
Published:	IEEE Access 2025
Subjects:	QE640-699 Stratigraphy SB183-317 Field crops Including cereals, forage crops, grasses, legumes, root crops, sugar plants, textile plants, alkaloidal plants, medicinal plants
Online Access:	https://eprints.ums.edu.my/id/eprint/43876/1/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/43876/ https://doi.org/10.1109/ACCESS.2025.3525661
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