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GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds

Deep learning models for rice pest detection often face performance degradation in real-world field environments due to complex backgrounds and limited computational resources. Existing approaches suffer from two critical limitations: (1) inadequate feature representation under occlusion and scale v...

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Principais autores: Fei Li, Yang Lu, Qiang Ma, Shuxin Yin, Rui Zhao
Format: Artigo
Sprog:Inglês
Udgivet: Frontiers Media S.A. 2025-08-01
Serier:Frontiers in Plant Science
Fag:
rice pest detection
GhostConv
context aggregation block
Shape-IoU
Slide Loss
Online adgang:https://www.frontiersin.org/articles/10.3389/fpls.2025.1620339/full
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