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Deep learning algorithms, particularly CNNs and Transformers, have shown superior efficiency and accuracy in pest detection and recognition tasks, significantly benefiting agricultural production. The paper outlines a systematic literature review on these algorithms, detailing methods for literature collection, common neural network architectures, public datasets, and challenges faced in the field. It emphasizes the importance of these technologies in enhancing crop protection and reducing pesticide use.

Author

M8Z

Language

EN