Analysis of Forest Pest Target Detection Method Based on YOLOv5s
This paper describes a forestry pest target detection method based on the YOLOv5s model,which is trained on a dataset of five types of forestry pests.The analysis of experimental results shows that the model can accurately detect and classify five types of pest images,including small targets,multiple targets,and normal conditions.In terms of image preprocessing,various data augmentation methods were used in the experiment,which effectively improved the model's generalization ability and robustness,and had a good detection effect on the proposed forestry pest target detection model.
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