A dual-track feature fusion model utilizing Group Shuffle Residual DeformNet and swin transformer for the classification of grape leaf diseases

Abstract Grape cultivation is important globally, contributing to the agricultural economy and providing diverse grape-based products. However, the susceptibility of grapes to disease poses a significant threat to yield and quality. Traditional disease identification methods demand expert knowledge,...

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Principais autores:	R. Karthik, Gadige Vishnu Vardhan, Shreyansh Khaitan, R. N. R. Harisankar, R. Menaka, Sindhia Lingaswamy, Daehan Won
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2024-06-01
Serier:	Scientific Reports
Fag:	Grape leaf disease Deep learning Dual-track network Swin transformer Triplet attention
Online adgang:	https://doi.org/10.1038/s41598-024-64072-x
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