SP-YOLO: A Real-Time and Efficient Multi-Scale Model for Pest Detection in Sugar Beet Fields

SP-YOLO: A Real-Time and Efficient Multi-Scale Model for Pest Detection in Sugar Beet Fields

Beet crops are highly vulnerable to pest infestations throughout their growth cycle, which significantly affects crop development and yield. Timely and accurate pest identification is crucial for implementing effective control measures. Current pest detection tasks face two primary challenges: first...

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Bibliographic Details
Main Authors: Ke Tang, Yurong Qian, Hualong Dong, Yuning Huang, Yi Lu, Palidan Tuerxun, Qin Li
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Insects
Subjects:
sugar beet pest
pest detection
multi-scale feature fusion
deep learning
intelligent pest management
Online Access:https://www.mdpi.com/2075-4450/16/1/102
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