Research on Insect-bitten Zijin Tea Detection Method Based on YOLOv5s-SE and Channel Pruning
In order to achieve rapid and accurate identification of insect-bitten Zijin tea leaves in complex nature backgrounds,a detection method for Zijin tea based on YOLOv5s-SE and channel pruning was proposed.Firstly,SE modules were added to the backbone network of YOLOv5s to enhance the model's feature extraction capability and reduce interference from complex backgrounds during tea leaf feature extraction.Then,a channel pruning algorithm was used to prune the model and fine-tuning was conducted,enabling fast and accurate detection of insect-bitten Zijin tea leaves.Compared to YOLOv5s,the test results showed that the pruned model reduced parameters by 60.1％,improved FPS by 18.6％,reduced GFLOPs by 29.7％,and achieved mAP of 81.3％.
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