现代信息科技2024，Vol.8Issue(1)：84-88,5.DOI:10.19850/j.cnki.2096-4706.2024.01.017
基于改进YOLOv7的滑雪摔倒检测
Ski Fall Detection Based on Improved YOLOv7
摘要
Abstract
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.关键词
目标检测技术/YOLOv7/滑雪摔倒检测/轻量化模型Key words
target detection technology/YOLOv7/ski fall detection/lightweight model分类
信息技术与安全科学引用本文复制引用
陈园林,高兴华,吴晗林..基于改进YOLOv7的滑雪摔倒检测[J].现代信息科技,2024,8(1):84-88,5.基金项目
吉林省科技发展计划项目(20220203179SF) （20220203179SF）
