Improved orchard grape detection algorithm of YOLOv8
Due to the low detection accuracy of existing orchard grape detection algorithms in the case of stem occlusion and fruit occlusion,an improved YOLOv8n orchard grape detection algorithm was proposed.Firstly,CA attention mechanism is intro-duced to the end of backbone network and neck network to improve the model's attention to key features.Then MPDIoU was used to replace the CIoU loss function in the original model to accelerate the convergence speed and improve the precision of bounding box regression.The experimental results show that the improved model has improved in P,R and mAP,and can meet the needs of grape detection in complex orchard environment.
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