Improved YOLOv7-Tiny for the Detection of Common Rice Leaf Diseases in Smart Agriculture

Improved YOLOv7-Tiny for the Detection of Common Rice Leaf Diseases in Smart Agriculture

Rapid and accurate detection of rice foliar diseases is essential for yield prediction and food security. This study proposes a multi-size rice leaf disease detection model, YOLOv7-tiny, for fast and accurate detection of rice leaf diseases. The MobileNetV3 lightweight network is introduced to repla...

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Bibliographic Details
Main Authors: Fuxu Guo, Jing Li, Xingcheng Liu, Sinuo Chen, Hongze Zhang, Yingli Cao, Songhong Wei
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Agronomy
Subjects:
rice disease
digital imaging
feature fusion
small target detection
Online Access:https://www.mdpi.com/2073-4395/14/12/2796

Internet

https://www.mdpi.com/2073-4395/14/12/2796

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