A Light Weight Detection Method of Litchi by Fusion of Attention Mechanism
In view of the characteristic of small size,dense growth and severe occlusion of litchi,in order to rapidly and accurately detect and count litchi fruits,a network model combining attention mechanism and multi-scale feature maps was proposed in this study.For the purpose of improving the recognition accuracy of fruit in occluding and shaded envi-ronments,Coordinate Attention(CA)mechanism was embedded in YOLOv4-Tiny model.In order to improve the detec-tion accuracy of the model for small target fruit,two larger scale feature maps were generated in the structure of Feature Pyramid Networks(FPN).The results showed that the Precision,Recall and mAP of the Litchi lightweight detection model combined with attention mechanism were 92.92%,76.09%and 88.51%,respectively.Compared with YOLOv4-Tiny and YOLOv3 models,the average detection accuracy of litchi lightweight detection model constructed in this paper with integrated attention mechanism was 8.84 percentage points and 3.87 percentage points higher,respec-tively.The model can detect litchi quickly and accurately in orchard environment,and suitable for identification and counting of litchi in orchard.
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