TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection

Tomatoes are one of the most economically significant crops worldwide, with their yield and quality heavily impacted by foliar diseases. Effective detection of these diseases is essential for enhancing agricultural productivity and mitigating economic losses. Current tomato leaf disease detection me...

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Veröffentlicht in:	Frontiers in plant science Jg. 16; S. 1530070
Hauptverfasser:	Wang, Rijun, Chen, Yesheng, Liang, Fulong, Mou, Xiangwei, Zhang, Guanghao, Jin, Hao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media SA 24.04.2025 Frontiers Media S.A
Schlagworte:	Accuracy Agricultural production Algorithms Blight Classification Crop diseases Datasets Deep learning Diffusion Disease detection Economic impact Efficiency EPMSC Feature extraction Foliar diseases Leaves MSFDNet Neural networks objection detection Plant diseases Plant Science Statistical analysis Target detection tomato disease Tomatoes deep learning EPMSC MSFDNet tomato disease objection detection
ISSN:	1664-462X, 1664-462X
Online-Zugang:	Volltext
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