Design of intelligent detection system for tobacco leaf pests based on deep learning
With the advancement of agricultural science and technology,the traditional pest monitoring methods can no longer meet the needs of modern agriculture.In order to improve the efficiency and quality of tobacco leaf production,this paper designs and implements an intelligent detection system for tobacco leaf pests based on deep learning.The system uses the advanced YOLOv7 target detection model and integrates functions such as data collection,deep learning training,and pest detection,can quickly and accurately identify insect pests on tobacco leaves,helping to intervene in early killing and protect the quality of tobacco leaves.The test results show that the system performs well in terms of real-time monitoring and accuracy,improving the efficiency of pest management.
deep learningtobacco pestsintelligent detectionartificial intelligence
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