High Frequency Workpiece Image Recognition Algorithm Based on Fusion of Multi Branch Network Structure
In order to effectively solve the problem of low recognition rate of high-frequency workpiece im-ages under complex illumination changes,this paper proposes a high-frequency workpiece image recogni-tion algorithm that integrates multi-branch network structure.The algorithm uses Efficient-b0 as the basic network.Firstly,a lightweight mixed attention module is introduced to extract the global workpiece image features with strong illumination robustness,and the global recognition result is obtained through the back-bone network;then,the weakly supervised area detection module is used to locate the workpiece The local important area is introduced into the branch network to obtain the local recognition result;finally,the global and local recognition results are combined in the branch fusion module to realize the artifact recognition.The experimental results show that,compared with various image recognition algorithms,the proposed algo-rithm has stronger adaptability to illumination changes,significantly improves the performance of high-fre-quency workpiece recognition,and the recognition accuracy reaches 97.8%.
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