Forest pest monitoring and prevention based on UAV image detection
In order to solve the problem of low efficiency and poor effect of existing pest control methods,which required a lot of man-power and material resources,the research built a forest pest detection framework based on deep learning,which transferred the fea-ture information extracted from the shallow network to the deep network,and made lightweight improvements to the model through pruning and batch normalization folding.The results showed that,when each model tended to be stable during training,the average ac-curacy of the improved YOLOv4 model reached 97.38%,and compared with the original YOLOv4 model,the computing cost and stor-age requirements were reduced by 17.81 percent points and 23.38%,respectively.The average detection accuracy was 12.75 percent points higher than before.
unmanned aerial vehicle(UAV)pest controlimage detectionYOLOv4 model
NETL
NSTL
万方数据
