Robotics & Machine Learning Daily News2024,Issue(Nov.19) :5-6.

Research from Nanjing Tech University in the Area of IntelligentSystems Publish ed (Fall detection method based on spatiotemporal coordinate attention for high -resolution networks)

南京理工大学智能化领域研究系统发布ed(基于时空坐标注意的高分辨率网络跌倒检测方法)

Robotics & Machine Learning Daily News2024,Issue(Nov.19) :5-6.

Research from Nanjing Tech University in the Area of IntelligentSystems Publish ed (Fall detection method based on spatiotemporal coordinate attention for high -resolution networks)

南京理工大学智能化领域研究系统发布ed(基于时空坐标注意的高分辨率网络跌倒检测方法)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于智能系统的最新研究结果已经发表。根据NewsRx记者从南京理工大学发回的新闻报道,研究称,“秋季”行为与老年人的高死亡率密切相关,跌倒检测具有重要意义是人类行为识别研究的热点。然而,现有的跌倒检测方法,在特征提取过程中,由于下采样导致细节动作信息丢失操作,当检测到具有类似行为的跌倒时,导致性能低于标准坐着

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on intelligent s ystems have been published. According tonews reporting originating from Nanjing Tech University by NewsRx correspondents, research stated, “Fallbehavior is cl osely related to the high mortality rate of the elderly, so fall detection has b ecome an importantand urgent research area in human behavior recognition. Howev er, the existing fall detection methods,suffer from the loss of detailed action information during feature extraction due to the downsamplingoperation, result ing in subpar performance when detecting falls with similar behaviors such as ly ing andsitting.”

Key words

Nanjing Tech University/Intelligent Sys tems/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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