A target improvement model based on YOLOv7 is proposed to address the current issues in detecting falls among skiers in ski resorts.For the problem of limited computing resources caused by deploying detection models on patrol robots,the Ghost model is introduced into the backbone network and GSConv is introduced in the neck to reduce model parameters;meanwhile,the Parallel Deformable Attention Conv(PDAC)module is introduced to enhance the accuracy of the model.The improved model has reduced parameters by 21.6%and GFLOPs by 27.7%compared to the original model,and the required computational resources have also been greatly reduced.
target detection technologyYOLOv7ski fall detectionlightweight model
国家科技期刊平台
NSTL
万方数据
维普
