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基于深度学习的老人摔倒检测设计

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老年人摔倒而未被及时发现已经成为危害老人生命安全的一个重大因素.随着我国老年人的生命安全保障问题越来越被重视,为了及时发现老人在家摔倒从而能尽早得到救治,提出了一种基于改进的YOLOv5 目标检测算法的老人摔倒识别检测设计.通过实验证明,该设计提升了算法识别精度,降低了漏检频率,使得其具有更好的识别检查功能.
Design of falling down Detection for the Elderly Based on Deep Learning
At present,the recognition technology of old people's falling down is immature,and the recognition effect is rela-tively poor.This paper proposes an elderly falling down recognition and detection system based on the enhanced YOLOv5 tar-get detection algorithm.It has been proven by experiments that this design has improved the algorithm recognition accuracy,reduced the frequency of missed inspection,and made the modified design has a better identification and inspection function.

deep learningthe elderly falling down detection analysisYOLOv5K-meansconvolutional neural network

赵俊、王玉珏、肖云峰、邓鸿伟

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南京理工大学紫金学院,江苏 南京 210023

深度学习 老人摔倒检测 YOLOv5 K-means 卷积神经网络

江苏省大学生创新创业训练计划(2023)

202313654047T

2024

工业控制计算机
中国计算机学会工业控制计算机专业委员会 江苏省计算技术研究所有限责任公司

工业控制计算机

影响因子:0.258
ISSN:1001-182X
年,卷(期):2024.37(4)
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