YOLOv11-RDTNet: A Lightweight Model for Citrus Pest and Disease Identification Based on an Improved YOLOv11n

YOLOv11-RDTNet: A Lightweight Model for Citrus Pest and Disease Identification Based on an Improved YOLOv11n

Citrus pests and diseases severely impact fruit yield and quality. However, existing object detection models face limitations in complex backgrounds, target occlusion, and small target recognition, and they struggle to be efficiently deployed on resource-constrained devices. To address these issues,...

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Bibliographic Details
Main Authors: Qiufang Dai, Shiyao Liang, Zhen Li, Shilei Lyu, Xiuyun Xue, Shuran Song, Ying Huang, Shaoyu Zhang, Jiaheng Fu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Agronomy
Subjects:
precision
deployment on mobile devices
deep learning
data augmentation
object detection
improved network
Online Access:https://www.mdpi.com/2073-4395/15/5/1252
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